DeepSeek vs Kimi is not a comparison between two fixed AI models. It is a choice between two expanding ecosystems: DeepSeek offers a focused consumer assistant, a first-party API, downloadable model weights and the open-source DeepSeek Harness; Kimi combines a consumer assistant with Deep Research, documents, spreadsheets, presentations, Kimi Work, Kimi Code and a separate developer platform. DeepSeek is the simpler starting point for focused chat and a comparatively inexpensive API workflow, while Kimi is the more natural starting point for research, office files and long-running knowledge-work tasks. Neither is the universal winner.
Independent-site disclosure: This comparison is not affiliated with DeepSeek, Moonshot AI or Kimi.
Full comparison reviewed: October 8, 2026. Regional API access, published price examples and Kimi privacy-source scope rechecked: October 15, 2026. Products, visible models, memberships, account credits, regional access and API prices can change. Check the current interface and official documentation before purchasing a plan, choosing a model or migrating a production workload.
Consumer-interface clarification: October 16, 2026. DeepSeek’s official iOS version history records the merged modes. This does not identify the exact backend for every current web session, region, or account, and does not change the separately documented API model list.
Evidence note: No matched hands-on benchmark was performed for this article. Task recommendations are based on current official product scope, documentation, prices, model cards and data policies. They should be treated as starting points for testing, not as invented evidence that one system produced a better answer in an unperformed experiment.
DeepSeek vs Kimi: the quick verdict
| Your priority | Better starting point | Why | Main qualification |
|---|---|---|---|
| Focused everyday chat | DeepSeek | Its main consumer experience is comparatively direct and centred on conversation, reasoning, coding and uploaded material. | A simpler product does not prove higher answer accuracy. |
| Research and source-heavy reports | Kimi | Kimi provides dedicated Search, Deep Research, Agent modes, plugins and access to specialised research workflows. | Citation count is not citation quality; every material claim still requires verification. |
| Word documents, spreadsheets and presentations | Kimi | Docs, Sheets, PPT and Kimi Work are explicit parts of the current product suite. | The downloaded deliverable must be checked for accuracy, format and editability. |
| Work directly with local folders and applications | Kimi Work | It is designed to read and write local files, use browsers, run commands and deliver documents, spreadsheets and slide decks. | “Local Agent” describes access to the computer; it does not necessarily mean all model inference occurs offline. |
| Open-source agent workspace | DeepSeek Harness | Harness is an MIT-licensed public-preview workspace with composable plugins for documents, data, code, research and automation. | It remains preview software, and several plugins are labelled experimental. |
| Repository-level coding | Test DeepSeek Harness and Kimi Code | Both can inspect files, edit code, run commands and support longer development workflows. | A fair decision needs the same repository, issue, permissions and tests. |
| Long-running multi-agent work | Kimi | Kimi Work documents Goal mode, scheduled work and Agent Swarm orchestration for large multi-step tasks. | More agents and tool calls do not automatically improve accuracy. |
| Low raw API token cost | DeepSeek Flash | Its current first-party list prices are low and include discounted off-peak rates. | Price per token is not price per correct completed task. |
| One-million-token multimodal API | Compare DeepSeek Flash and Kimi K3 | Both document one-million-token contexts and visual input, but their reasoning controls, media support, prices and tool ecosystems differ. | Maximum context does not prove reliable use of every token. |
| Video understanding through an API | Kimi | Current Kimi API documentation lists text, image and video input for K3, K2.7 Code and K2.6. | Video understanding is different from video generation. |
| Confidential or regulated information | No brand-level winner | Consumer, API, custom-provider, business and self-hosted routes have different data terms. | Review the agreement and full data path for the exact route being used. |
The practical difference is therefore not simply “DeepSeek is better at reasoning” or “Kimi is better for documents.” DeepSeek and Kimi should be compared by product layer and task.
What exactly is being compared?
Each brand contains several products. Putting all of them into one feature table can create misleading conclusions.
| Product layer | DeepSeek route | Kimi route | Fair comparison |
|---|---|---|---|
| Consumer assistant | DeepSeek web and mobile assistant | Kimi web and mobile assistant | Compare signed-in consumer accounts under recorded models, modes and tool settings. |
| Research workflow | Consumer search where available, or research inside DeepSeek Harness | Kimi Search, Deep Research, Agent modes and Kimi Work | Use the same research question, date range, source rules and validation method. |
| Knowledge-work agent | DeepSeek Harness | Kimi Work | Compare local files, browser tasks, documents, spreadsheets, presentations, permissions and repair effort. |
| Coding agent | DeepSeek Harness or a coding agent using a DeepSeek API model | Kimi Code CLI, Kimi Code for VS Code or a compatible external agent | Use identical repository snapshots, tests and approval rules. |
| First-party API | DeepSeek API Platform | Kimi API Open Platform, with separate international and mainland China routes | Compare exact model IDs, regional platforms, key types, currencies, modalities, tools, context, latency and verified task quality. |
| Membership-based coding access | No directly equivalent product should be assumed | Kimi Code membership API and official clients | Do not compare a membership allowance with DeepSeek pay-as-you-go pricing without explaining the billing difference. |
| Open-weight model | Official DeepSeek checkpoints | Official Moonshot/Kimi checkpoints | Compare exact model cards, licenses, quantisation and hardware requirements. |
| Third-party deployment | External providers can host DeepSeek models | External providers can host Kimi models | Do not attribute a third party’s price, speed, privacy or configuration to the first-party service. |
A Kimi Work result should not be compared with an ordinary DeepSeek chat response when the task involves local files and command execution. The closer match is DeepSeek Harness. Likewise, Kimi Code should be compared with a repository-capable agent, not with a model answering a pasted code snippet.
Official access routes
| Ecosystem | Official route | Purpose | Important check |
|---|---|---|---|
| DeepSeek consumer assistant | Official DeepSeek chat | Conversation, reasoning, coding questions and supported file workflows | Record the visible mode and current account controls. |
| DeepSeek downloads | Official DeepSeek download page | Verified mobile application links and consumer access | Avoid similarly named unofficial applications. |
| DeepSeek Harness | Official Harness page | Documents, data, coding, research, plugins, automation and local workspaces | It is currently a public-preview product. |
| DeepSeek API | Official API documentation | Hosted model access through OpenAI- and Anthropic-compatible formats | Check the current model ID and peak or off-peak price. |
| Kimi consumer assistant | Kimi website (kimi.ai) and Kimi website (kimi.com) | Chat, search, research, uploaded files, Docs, Sheets, PPT, Build and Agent tasks | Features and credits vary by account; review the consumer policy linked to your account. |
| Kimi Work | Official Kimi Work documentation | Local folders, browser operations, commands, long-running tasks and finished work products | Use conservative permissions until the workflow is understood. |
| Kimi Code | Official Kimi Code documentation | Terminal, VS Code and compatible external coding-agent workflows | Official-client login and third-party API-key access use different authentication methods. |
| Kimi API — international | International Kimi API quickstart | General pay-as-you-go API route for supported users outside mainland China | Use the international account, key and API endpoint together; Kimi Code and consumer membership are separate products. |
| Kimi API — mainland China | Mainland China Kimi API reference | Regional Open Platform with a published Chinese-yuan pricing schedule | Its accounts, balances and API keys are separate from those of the international platform. |
The international API FAQ directs users outside mainland China to platform.kimi.ai, but still qualifies access by supported region and network conditions. Confirm availability and payment options for the intended account; an international platform is not a guarantee of access in every country.
Current products and models
Old comparisons centred on DeepSeek R1 and Kimi K1.5 or K2 are no longer sufficient. Current products and aliases need to be checked at the time of testing.
| Route | Current documented position | What not to assume |
|---|---|---|
| DeepSeek consumer app | The official app is presented as using DeepSeek’s latest flagship model. Expert Mode appeared in earlier V4-era guidance; the iOS release notes later merged Instant, Expert, and Vision modes in September 2026. Follow the current interface for your platform rather than assuming that selector remains available. | Do not assign an exact permanent API checkpoint to every consumer conversation. |
deepseek-flash | Currently maps to DeepSeek-V4.1-Flash, with text and image input, one-million-token context and thinking or non-thinking operation. | Legacy Flash names that still resolve are not separate current models. |
deepseek-v4-pro | Currently maps to DeepSeek-V4-Pro-0813 and remains available after DeepSeek reversed an earlier phase-out decision. | It does not currently provide the same visual-input support as Flash. |
| DeepSeek Harness | Open-source MIT software in worldwide public preview, with several plugins marked experimental. | A Harness feature is not automatically a capability of the base model alone. |
| Kimi consumer product | Current documentation centres on K3-era chat and Agent workflows, alongside Docs, Sheets, PPT, Deep Research and Build. | The visible mode does not necessarily identify an exact dated API checkpoint. |
kimi-k3 | Kimi’s current flagship API model, with one-million-token context, native vision and configurable reasoning effort. | K3 uses thinking mode; it should not be compared with a non-thinking model without disclosure. |
kimi-k2.7-code | A coding-focused API model with a 256K context window and text, image and video input. | It is not the same product as Kimi Code. |
kimi-k2.6 | A general model with text, image and video input and both thinking and non-thinking behaviour. | An older Kimi model name should not be used simply because it remains in an old tutorial. |
kimi-for-coding | A fixed model ID used by the membership-based Kimi Code API; its backend can be upgraded without changing the client configuration. | It is not the same billing route as the normal pay-as-you-go Kimi API. |
For reproducible testing, record the exact visible product, mode, account and date. A floating alias can change without the client changing its model string.
Consumer app comparison
| Dimension | DeepSeek | Kimi |
|---|---|---|
| Product focus | A comparatively focused assistant for conversation, reasoning, coding and supported file tasks | A broader knowledge-work suite combining chat, research, files, office artifacts, websites and Agent workflows |
| Free consumer access | The official application is publicly presented as free. | Kimi provides a free allowance, while heavier Agent, research, PPT and coding tasks consume credits; paid memberships and extra usage are available. |
| Web research | Research and source verification are explicitly documented in DeepSeek Harness; confirm current consumer search controls in the live app. | Search, Deep Research, plugins, databases and Agent modes are first-class parts of the current product suite. |
| Files | The consumer service accepts user-provided files; Harness works with documents, spreadsheets, code and local workspaces. | Kimi supports uploaded documents and media; Kimi Work can read and write authorised local folders. |
| Documents and spreadsheets | Harness can draft, inspect and modify document and spreadsheet files. | Dedicated Docs and Sheets workflows are supported alongside Kimi Work. |
| Presentations | Harness documents slide creation and revision within its workspace. | Kimi provides dedicated PPT workflows, visual slide generation and presentation creation through Kimi Work. |
| Local system access | Harness uses workspaces, tools, plugins and command execution. | Kimi Work is explicitly built around local files, browser operations, commands and desktop tasks. |
| Long-running work | Harness supports background and scheduled tasks, with some automation plugins currently experimental. | Kimi Work provides Goal mode, scheduled tasks and documented long-horizon execution. |
| Multi-agent orchestration | Harness lists Agent teams as experimental. | Kimi Work documents Agent Swarm orchestration with up to 300 sub-agents. |
| Coding product | DeepSeek Harness | Kimi Code CLI, Kimi Code for VS Code and compatible external agents |
| Projects and continuity | Harness provides workspaces and reusable sessions. | Kimi provides Projects, Memory, Work projects, dashboards and saved coding sessions. |
Kimi has the broader documented consumer and knowledge-work product suite. DeepSeek’s advantage is not a larger feature catalogue; it is a more focused assistant plus an open-source, extensible Harness and comparatively straightforward API route.
Which is better for everyday chat and writing?
DeepSeek is the simpler starting point for focused chat. A user who mainly wants explanations, rewriting, brainstorming, coding questions or file-based questions may not need Kimi’s larger collection of Agent, office and desktop features.
Kimi is the more flexible starting point when the conversation may turn into a deliverable. A request can move from research to a document, spreadsheet, presentation, website or longer Agent task within the same product ecosystem.
This is a difference in product scope, not proof that one writes more accurately. A fair writing comparison should use the same audience, purpose, facts, length and style constraints.
A useful matched writing test
- Choose one real but non-sensitive writing task.
- Define the intended reader, purpose, required facts, tone, length and prohibited claims.
- Use fresh conversations and disable unrelated tools where possible.
- Record the account, visible model or mode and date.
- Preserve the first completed answer.
- Score factual accuracy separately from fluency and style.
- Give both systems the same focused correction request.
- Choose the result that reaches a verified publishable state with less repair.
Which is better for reasoning and mathematics?
There is not enough matched evidence here to name an overall reasoning winner. DeepSeek’s current API models support thinking and non-thinking modes, while Kimi K3 uses thinking with adjustable reasoning_effort. Different default modes alone can change answer length, latency and cost.
Vendor benchmarks should not settle the decision. DeepSeek and Moonshot AI use their own prompts, scaffolds, models, tools and evaluation settings. Scores produced under different harnesses are not a controlled head-to-head test.
How to compare a reasoning answer
- Define the independently verified final answer before testing.
- Use identical wording, numbers, units and constraints.
- Match tool access and reasoning settings as closely as possible.
- Check the final answer rather than rewarding a longer explanation.
- Recalculate every material step independently.
- Test several different problems before making a purchasing decision.
Which is better for web research and citations?
Kimi is the more obvious first test for a packaged research workflow. Its current ecosystem includes Search, Deep Research, professional data sources, plugins, Agent modes and Kimi Work. These tools are designed to move from a research request to a longer report or other work product.
DeepSeek Harness is the relevant DeepSeek route when research needs to interact with local files, code, spreadsheets or repeatable automation. Its official scope includes finding information, verifying facts and citing sources.
Neither should be judged by the number of displayed citations. A real source can be attached to a sentence it does not fully support.
Verify an AI research report
- Identify the claims that materially affect the conclusion.
- Open the source attached to each claim.
- Confirm that the source supports the complete sentence.
- Check the publication date and event date separately.
- Check geography, period, sample, currency, units and definitions.
- Prefer original studies, filings, laws, statistics and official documentation.
- Look for credible evidence that challenges the report’s conclusion.
- Cite the original source rather than citing the generated report.
Which is better for PDFs and long documents?
Both ecosystems provide document workflows, but the relevant products are different. The DeepSeek consumer assistant can answer questions about uploaded material, while Harness extends the workflow to local workspaces and generated files. Kimi supports uploaded files in the web product, persistent reference material in Projects and direct local-folder access through Kimi Work.
| Document task | DeepSeek route | Kimi route | Main risk |
|---|---|---|---|
| Ask questions about one PDF | DeepSeek consumer assistant | Kimi consumer assistant | Correct fact with an incorrect page reference |
| Research across uploaded documents and the web | DeepSeek Harness | Kimi Deep Research or Agent mode | Web evidence and file evidence can be mixed without clear labels. |
| Work with many local files | Harness workspace | Kimi Work authorised folder | Overwriting files, incorrect batch changes or unintended access |
| Persistent project context | Harness sessions and workspace | Kimi Projects, Memory or Work projects | Old instructions or files may influence a later answer. |
| API-based PDF questions | Use a verified parsing route before sending extracted content to a DeepSeek model. | Kimi API provides a documented file workflow and PDF-question guide. | Parser, OCR and model errors are separate failure points. |
Run a fair PDF test
- Use the same small searchable PDF in fresh sessions.
- Define the correct answers and source pages before uploading.
- Include one requested fact that is intentionally absent.
- Require “Not stated” instead of allowing inference.
- Score factual extraction and page attribution separately.
- Check table transcription before checking arithmetic.
- Test an image-only scan separately only when OCR-like performance matters.
A one-million-token context window does not guarantee that every page of a long file is extracted correctly, recalled later or attributed to the correct source.
Which is better for documents, spreadsheets and presentations?
Kimi is the better first product to evaluate for office-style deliverables. Its current product structure includes dedicated Docs, Sheets and PPT workflows, while Kimi Work can read local files and produce documents, spreadsheets and slide decks directly in an authorised workspace.
DeepSeek Harness is a meaningful alternative. It documents workflows involving DOCX, XLSX, PDF, HTML, code and slides, with conversational revision inside the workspace. However, Harness is still in public preview, and some automation features are experimental.
Inspect the file, not only the chat preview
- Download and open the actual file.
- Confirm its extension, format, page count or slide count.
- Check whether text, cells, shapes and charts are individually editable.
- Verify spreadsheet formulas and recalculated results.
- Confirm that chart geometry matches its labels and source values.
- Test hyperlinks, speaker notes, fonts and exports.
- After a correction, recheck unaffected pages, sheets and slides for unintended changes.
A PPTX can technically open in PowerPoint while containing only one flattened image per slide. That is not equivalent to a native deck with editable text boxes, charts and shapes.
DeepSeek vs Kimi for coding
Both consumer assistants can explain code, generate functions and discuss errors. Repository-level development requires a different comparison: DeepSeek Harness vs Kimi Code.
| Dimension | DeepSeek Harness | Kimi Code |
|---|---|---|
| Product status | Open-source worldwide public preview | Official Kimi coding service available through CLI, VS Code and compatible external agents |
| Primary scope | Coding plus documents, data, research, plugins and general workspace tasks | Software-development and terminal workflows |
| Interfaces | Desktop application or locally launched web interface | CLI, VS Code and supported third-party coding agents |
| Repository access | Reads and edits workspace files, runs commands and tests | Reads and edits code, runs shell commands, searches the web and plans tasks |
| Extensibility | Composable plugin architecture, skills, tools, subagents and experimental Agent teams | CLI customisation, IDE integration, compatible external agents and current platform tools |
| Authentication | DeepSeek account for official models or user-configured custom provider | OAuth in official clients or a Kimi Code API key for compatible external tools |
| Model selection | Official DeepSeek model or configured custom provider | Managed kimi-for-coding and optional HighSpeed tier under current membership rules |
| Source licence | MIT-licensed Harness software | Check the licence and terms of the exact Kimi Code component and service being used. |
| Best starting user | A developer who wants an inspectable, extensible workspace and accepts preview maturity | A developer who wants a dedicated coding product with terminal and VS Code support |
Kimi Code’s managed model can be upgraded behind the fixed kimi-for-coding identifier. DeepSeek Harness can use official DeepSeek services or a custom model provider. That flexibility makes version, provider and data-path disclosure essential in any coding comparison.
Repository-level test protocol
- Create identical clean branches or worktrees.
- Use the same issue, acceptance criteria and test suite.
- Match network access and available tools.
- Start with command and file-change approvals enabled.
- Ask each agent to inspect the repository and propose a plan before editing.
- Preserve the first plan and first patch.
- Run the same tests, type checks and static analysis.
- Inspect every changed file and unintended modification.
- Give each tool one identical correction request.
- Compare human repair effort, cost and time to a reviewed patch.
Passing a small test suite does not prove that a patch is secure, maintainable or production-ready. Human code review and security review remain necessary.
Which is better for agents and long-running tasks?
Kimi currently documents the more expansive long-horizon product stack. Kimi Work can divide tasks into parallel steps, use local files, operate a browser through WebBridge, run scheduled work and use Goal mode. Its documentation also describes Agent Swarm orchestration involving up to 300 sub-agents.
DeepSeek Harness takes a modular approach. Its “everything is a plugin” architecture can extend tools, skills and interfaces. Scheduled tasks, Agent teams and automatic approval review are currently labelled experimental.
See our DeepSeek Harness setup guide for model-provider configuration and permission checks.
More autonomy requires more controls
- Begin in a copied project or disposable workspace.
- Limit the folders and applications the agent can access.
- Require approval for destructive commands, overwrites, purchases and external submissions.
- Do not expose API keys, password stores or production credentials.
- Review plugins, Skills, MCP servers and browser extensions separately.
- Define objective acceptance evidence before starting a long task.
- Stop the workflow when evidence is missing rather than allowing the agent to invent completion.
A task completed by 300 sub-agents is not automatically better than a task completed by one agent. Orchestration adds cost, coordination risk and additional opportunities for unsupported claims.
Images, video and multimodal work
Kimi currently has the broader documented multimodal API route. Its current K3, K2.7 Code and K2.6 documentation supports text, image and video input. DeepSeek-V4.1-Flash accepts text and images, while the current V4 Pro API route is text-only.
| Need | Better starting point | Reason | Qualification |
|---|---|---|---|
| Analyze a screenshot or image | Test both | Current DeepSeek Flash and Kimi API models support visual input. | Use the same image and predefined questions. |
| Understand a video | Kimi | Current Kimi API documentation explicitly supports video input. | Check file limits, frame coverage and timestamp accuracy. |
| Analyze visual feedback during coding | Kimi K3 or K2.7 Code is a relevant candidate | Kimi documents image and video input for coding-oriented models. | A multimodal model is not automatically a better coding agent. |
| Generate images or video | Use a verified specialised product | Understanding media and generating media are different capabilities. | Do not infer generation support from visual-input support. |
Free access, memberships and consumer costs
“Is DeepSeek or Kimi free?” has no one-word answer because consumer access, agents, memberships and APIs are billed separately.
| Route | Current cost structure | What it includes | Main caveat |
|---|---|---|---|
| DeepSeek consumer assistant | Publicly presented as free | Hosted consumer chat and current supported features | Free access does not promise unlimited usage or free API calls. |
| DeepSeek Harness software | Open source under MIT | The Harness application and plugin architecture | Official model usage, custom-provider usage and infrastructure can still cost money. |
| DeepSeek API | Pay-as-you-go token billing | Current Flash and Pro API models | Peak and off-peak prices differ. |
| Kimi consumer product | Free allowance with account credits | Chat and a limited amount of Agent, research, PPT, coding and related work | Complex or long tasks consume more credits. |
| Kimi membership | Paid membership with a shared credit pool | Expanded use across eligible features such as Deep Research, PPT, Kimi Work and Kimi Code | Unused monthly credits currently expire rather than roll over. |
| Kimi extra usage | Additional usage packs | More capacity after the included allowance is consumed | Check the current account price, currency and expiry terms. |
| Kimi Code membership API | Included usage under current Kimi Code membership rules | Official clients and compatible external coding agents | This allowance is separate from the normal pay-as-you-go Kimi API. |
| Kimi API — international | Pay-as-you-go; published prices in US dollars (USD) | Model inference and separately priced tools on the international Open Platform | Use its own funded account and current model-access rules; membership benefits are not API balance. |
| Kimi API — mainland China | Pay-as-you-go; published prices in Chinese yuan (CNY) | Model inference and tools on the mainland China Open Platform | Account funding, model eligibility and tool charges follow this regional platform’s rules. |
Kimi’s official documentation is actively evolving, including changes to membership and Kimi Code benefits. Use the signed-in subscription screen rather than relying on an older plan name or copied price.
DeepSeek API vs Kimi API
Both platforms support OpenAI-compatible requests, and both document Anthropic-compatible routes. Their current models, reasoning controls, modalities, billing currencies and product goals differ. The Kimi column below distinguishes its international and mainland China Open Platforms. A developer-console URL is not the same thing as an API base URL.
| Dimension | DeepSeek API | Kimi API — regional platforms |
|---|---|---|
| Chat Completions base URL | https://api.deepseek.com | International: https://api.moonshot.ai/v1Mainland China: https://api.moonshot.cn/v1 |
| Anthropic-compatible base URL | https://api.deepseek.com/anthropic | International: https://api.moonshot.ai/anthropicMainland China: https://api.moonshot.cn/anthropic |
| Current general starting model | deepseek-flash | kimi-k3 |
| Premium or specialised route | deepseek-v4-pro | kimi-k2.7-code, kimi-k2.7-code-highspeed or kimi-k2.6, depending on the task |
| Maximum documented context | 1M for current Flash and Pro | 1M for K3; 256K for current K2.7 Code and K2.6 |
| Maximum documented output | 384K for current Flash and Pro | Check the exact current model page and provider limit. |
| Images | Flash supports image input; Pro currently does not. | K3, K2.7 Code and K2.6 support image input. |
| Video input | Not documented for the current Flash or Pro route | Documented for K3, K2.7 Code and K2.6 |
| Reasoning control | Thinking can be enabled or disabled, with adjustable effort. | K3 always thinks and supports low, high or max effort; K2.6 supports thinking and non-thinking behaviour. |
| Structured output | JSON output is documented. | JSON and schema-constrained structured output are documented. |
| Tools | Tool calls, Responses API and agent integrations | Tool calls, Responses API, search tools, file resources and agent workflows |
| Context caching | Automatic cache-hit pricing | K3 automatically caches eligible prefixes, with a five-minute default or one-hour TTL and distinct cache-read and cache-write billing. |
| Billing currency | US dollars on the referenced pricing page | International Open Platform: USD. Mainland China Open Platform: CNY. |
Endpoint references: international API overview and mainland China API overview. The .cn endpoint is an official regional route, not an invalid or unofficial address. For an international setup walkthrough, see our Kimi API guide.
Match the key to the platform. The regional authentication FAQ states that regional accounts, balances and keys are independent. A cross-region key can produce 401 invalid_authentication_error. That is not proof of a country block: also check the key itself and authentication header against the API error reference. Kimi Code keys and consumer membership benefits are not interchangeable with general Open Platform access.
Published list-price examples by platform
The published examples below were checked in the linked official sources on October 15, 2026. US-dollar and Chinese-yuan prices are separate regional schedules, not currency conversions. These are token-price examples, not total quotes for a completed task; account terms, taxes, tools, caching and retries can affect the bill.
| Model, platform and condition | Uncached input per 1M tokens | Cached input per 1M tokens | Output per 1M tokens | Additional rule / cache-write rate |
|---|---|---|---|---|
deepseek-flash, off-peak | US$0.15 | US$0.003 | US$0.60 | Off-peak applies outside the documented weekday peak windows. |
deepseek-flash, peak | US$0.30 | US$0.006 | US$1.20 | Peak windows are 01:00–04:00 and 06:00–10:00 UTC, Monday–Friday, excluding Chinese public holidays. |
deepseek-v4-pro, off-peak | US$0.66 | US$0.022 | US$1.98 | Text-only on the current documented route. |
deepseek-v4-pro, peak | US$1.32 | US$0.044 | US$3.96 | Continues to be offered after an earlier planned phase-out. |
kimi-k3 — international (USD) | US$3.00 | US$0.30 | US$15.00 | Per 1M cache-write tokens: US$3.00 with a five-minute TTL; US$6.00 with a one-hour TTL. |
kimi-k3 — mainland China (CNY) | CN¥20 | CN¥2 | CN¥100 | Per 1M cache-write tokens: CN¥20 with a five-minute TTL; CN¥40 with a one-hour TTL. |
Price sources: DeepSeek figures come from its current pricing reference. Kimi input and cache rates are documented in the international caching guide and mainland China caching guide; output examples are published in the international K3 announcement and Chinese K3 announcement. Recheck the international price schedule or mainland China price schedule before budgeting. The international pricing page excludes applicable taxes.
Avoid double-counting K3 input. Cache writes are a distinct billing category, not a second cache-miss charge on the same token. In Chat Completions and Responses usage, uncached input, cache reads and cache writes are mutually exclusive portions of total input. Apply each rate to its own token count, not both input and write rates to the entire prompt. The linked caching guides document automatic five-minute caching and the optional one-hour TTL.
Kimi also prices some tools separately; its international search-price reference distinguishes successful Basic and Pro search calls. The K3 quickstart currently warns that web search is being updated and is not recommended in the near term, so confirm readiness for the exact integration rather than treating a published price as an availability guarantee. DeepSeek’s off-peak rates can reduce the cost of workloads that can be scheduled flexibly.
Which API should you test first?
- Start with DeepSeek Flash when raw token cost, long output, one-million-token context or visual input at a low list price is the main priority.
- Start with Kimi K3 when the application needs one-million-token context, image or video understanding, long-horizon knowledge work or the Kimi tool ecosystem.
- Evaluate DeepSeek Pro when the text-only premium route produces enough measurable quality improvement to justify its higher price.
- Evaluate Kimi K2.7 Code for coding-agent workloads where its coding focus and video or image input are useful.
- Run a representative evaluation before moving production traffic. The cheapest request can become the most expensive workflow if it needs repeated correction.
Open-weight models and local deployment
Both ecosystems publish downloadable weights, but their current frontier models are extremely large. “Open weight” does not mean easy to run on a laptop, and it does not mean that the hosted consumer product can be reproduced by downloading one repository.
| Model | Current official description | Local implication | Licence check |
|---|---|---|---|
| DeepSeek-V4.1-Flash | 552B-parameter multimodal Mixture-of-Experts model with 8B active parameters during input processing, 16B during output generation and up to one-million-token context | The full weights remain server-class despite the lower active-parameter count. | Read the exact official model card and licence before commercial deployment. |
| Kimi K3 | 2.8T-parameter Mixture-of-Experts model with 104B activated parameters, native vision and one-million-token context | The official frontier checkpoint requires substantial storage and distributed-compute planning. | The official repository uses the Kimi K3 licence rather than assuming a standard permissive licence. |
Activated parameters describe computation per token; they do not describe total weight storage. A model with 8B or 104B active parameters can still require access to hundreds of billions or trillions of total parameters.
Local deployment still has costs
- GPU or accelerator hardware
- System RAM, VRAM and storage
- Quantisation and runtime engineering
- KV-cache memory for long context
- Electricity or cloud rental
- Monitoring, security and backups
- Model updates and licence review
- Search, tools, file parsing and sandbox infrastructure
A local interface can also call remote search services, MCP servers, cloud embeddings or hosted models. Verify the complete data path before calling a setup private or offline.
Privacy and data handling
Privacy should be compared by the exact product, account and applicable policy rather than by company name alone. The regional API labels above identify developer platforms, keys and billing; they do not, by themselves, establish where every consumer or API record is processed or stored.
| Route | Current documented treatment | Practical action |
|---|---|---|
| DeepSeek consumer service | The current policy covers prompts, voice input, uploaded files, photos, outputs and chat history. It describes service-improvement and training uses, an opt-out right, and direct processing and storage in the People’s Republic of China. | Do not submit sensitive material by default; review history, deletion and training opt-out controls. |
| DeepSeek Harness with official models | Harness documents collection of session logs, inputs, uploads, outputs, tool calls, plugin configuration and conversation data. Users can request an opt-out from model-training use. | Treat an official-model Harness session as hosted processing rather than a fully local private workflow. |
| DeepSeek Harness with a custom provider | The Harness policy says input is sent directly to the configured model provider and that Harness does not store or process that input and output server-side. | Review the custom provider, local logs, plugins, tools and MCP servers separately. |
| Kimi consumer accounts covered by the kimi.ai policy | The kimi.ai Privacy Policy names NOVASCENT PRIVATE LIMITED as provider and controller. It describes user-content processing for service delivery and improvement, including model training, and permits transfer and storage outside the user’s country of residence. | Check this policy and your account’s controls. It does not establish one exclusive storage country for all international users. |
| Kimi consumer guidance published on kimi.com | The kimi.com data-usage help page says de-identified conversations may be used for training, describes an account-level opt-out through support, and states that data is stored in mainland China. | Apply those details only where that guidance governs your service. Do not automatically extend its storage or opt-out statements to every Kimi account. |
| Kimi API — regional security guidance | API-specific security guidance on kimi.ai and kimi.com says submitted API inputs and outputs are not used to train or improve Kimi models. Both describe uploaded-file deletion controls. | No-training language is not a blanket zero-retention or data-residency guarantee. Review the applicable regional agreement, file handling and enterprise terms. |
| Kimi Work | Kimi Work can read and write authorised local files, run commands and operate a browser according to the selected permission level. | Start with approval prompts, restrict the workspace and review every destructive or external action. |
| Self-hosted model | Inference can run on infrastructure controlled by the user. | Audit downloads, telemetry, web tools, remote plugins, logs and exposed endpoints before claiming privacy. |
Do not upload passwords, API keys, identity documents, medical records, customer data, employee files, confidential contracts, trade secrets, unreleased financial information or privileged legal material without explicit authorisation for the exact service route.
Who should choose DeepSeek?
- A user who wants a focused consumer assistant without first choosing among a large collection of office and Agent products.
- A developer prioritising low first-party API token prices.
- A team that can schedule API traffic around off-peak rates.
- A developer who wants one-million-token context and unusually long documented output limits.
- A user willing to evaluate an open-source public-preview Harness for coding, data, documents and automation.
- An organisation with the infrastructure to evaluate a large DeepSeek open-weight model.
DeepSeek is less compelling when the main requirement is a mature suite of dedicated consumer products for Deep Research, presentations, spreadsheets, local desktop work and managed coding membership.
Who should choose Kimi?
- A researcher who wants Search, Deep Research, Agent workflows and specialised data sources in one ecosystem.
- A knowledge worker producing documents, spreadsheets, presentations and interactive outputs.
- A desktop user who wants an Agent to work directly with authorised local folders and browser tasks.
- A developer who prefers a dedicated CLI or VS Code coding product with managed membership access.
- An API developer who needs text, image and video understanding from the same current model family.
- A team evaluating long-running tasks, Goal mode or multi-agent orchestration.
Kimi is less compelling when the user needs only a simple chat workflow or when its membership, credit and product distinctions add unnecessary complexity.
Should you use both?
Using both can make sense when their roles are defined. Agreement between two AI systems is not independent verification, so one model should not be treated automatically as the fact-checker for the other.
- Use DeepSeek for cost-sensitive extraction, classification or focused text processing.
- Use Kimi when the task must become a document, spreadsheet, deck, website or long-running Agent workflow.
- Use original sources to verify research claims.
- Use calculators or spreadsheets to verify arithmetic.
- Use tests and code review to verify software changes.
- Record which product, model and tool produced each part of a final deliverable.
How to run your own fair DeepSeek vs Kimi test
- Choose one representative task. Use real but non-sensitive work that could affect your decision.
- Compare equivalent products. Use app versus app, Harness versus Work, Harness versus Code or API versus API.
- Record the setup. Note date, country, account, plan, visible model, mode, tools, search and permissions. For API tests, also record the regional platform and endpoint.
- Define success before testing. Write the correct facts, required calculations, file format, tests and prohibited behaviour.
- Use identical source material. Supply the same files, prompt, scope and output requirements.
- Preserve first outputs. Keep failures, refusals, partial files and incorrect calculations.
- Validate everything important. Open sources, recalculate values, run tests and inspect downloaded files.
- Send one matched correction. Give both systems the same opportunity to repair the highest-impact defect.
- Measure repair effort. Count factual corrections, formatting repair, code changes and manual rebuilding.
- Record cost and time. Include subscriptions, API tokens, search calls, tools, retries and human review.
- Repeat only when necessary. Add another task only if it represents a materially different workflow.
| Evaluation dimension | What to measure |
|---|---|
| Accuracy | Correct facts, calculations, code behaviour, dates, labels and units |
| Completeness | Whether every requested field, section, test or file was delivered |
| Instruction following | Compliance with scope, format, exclusions and source restrictions |
| Source quality | Primary sources, citation-to-claim fit, freshness and treatment of disagreement |
| Deliverable quality | Whether the document, spreadsheet, deck, website or code opens and remains usable |
| Repair effort | Time and number of corrections required before use |
| Latency | Time to a verified usable result, not merely time to the first answer |
| Cost | Membership, API, tools, retries, infrastructure and staff time |
| Privacy fit | Whether the selected route is appropriate for the actual information |
| Operational fit | Availability, permissions, integrations, reliability, monitoring and support |
Limitations of this comparison
- No matched hands-on quality test was conducted for this article.
- Consumer applications can change backend models without exposing exact dated checkpoints.
- Kimi Skills, plugins, memberships and Agent modes can materially affect results.
- DeepSeek Harness is still a preview product, and some plugins are experimental.
- Official benchmarks use vendor-selected settings and should not be treated as independent head-to-head tests.
- One-million-token context does not guarantee complete long-document recall.
- API performance varies by model, provider, reasoning effort, tools, request length and date.
- A quantised local deployment should not be assumed to match a first-party hosted service.
- Free limits, memberships, credits, prices and regional access can change.
- Privacy terms differ across regional consumer and API services, official-model, custom-provider, business and self-hosted routes.
Neither DeepSeek nor Kimi should be the sole authority for medical, legal, financial, compliance, academic or safety-critical decisions. Verify original evidence and obtain qualified review where appropriate.
Frequently asked questions
What is the main difference between DeepSeek and Kimi?
DeepSeek combines a focused consumer assistant, low-cost first-party API, open-weight models and the open-source DeepSeek Harness. Kimi provides a broader knowledge-work suite that includes chat, Search, Deep Research, documents, spreadsheets, presentations, Kimi Work, Kimi Code and long-running Agent workflows.
Is DeepSeek better than Kimi?
Not for every task. DeepSeek is a sensible first choice for focused chat and cost-sensitive API use. Kimi is the stronger starting point for research, office artifacts, local desktop workflows and managed long-running Agents. Answer quality requires a matched test.
Which is better for coding?
Both can answer coding questions. For repository work, compare DeepSeek Harness with Kimi Code under the same repository, issue, tests, permissions and model settings. Harness is an extensible open-source preview, while Kimi Code is a dedicated managed coding product with CLI and VS Code support.
Which is better for research?
Kimi is the clearer first test for a packaged Search and Deep Research workflow. DeepSeek Harness is relevant when research must interact with local files, code, spreadsheets, plugins or scheduled tasks. Verify every important citation in either result.
Which is better for PDFs and long documents?
Both support document workflows. Kimi offers a broader set of Projects, research and local-file tools, while DeepSeek offers consumer file questions and Harness workspaces. Use the same test file and score factual extraction, missing-information handling and page references separately.
Which is better for Word, Excel and PowerPoint files?
Kimi is the more natural first choice because Docs, Sheets, PPT and Kimi Work are dedicated parts of its current product. DeepSeek Harness can also work with documents, spreadsheets and slides. Inspect the downloaded file rather than relying on the preview.
What is the difference between DeepSeek Harness and Kimi Work?
Both are broader Agents rather than ordinary chat boxes. DeepSeek Harness is an MIT-licensed, plugin-based public-preview workspace for documents, data, code, research and automation. Kimi Work is a desktop Agent for knowledge workers that directly handles authorised local files, browser tasks, commands and office deliverables.
Is DeepSeek free?
The official consumer assistant is publicly presented as free. DeepSeek API usage is billed separately, and using hosted models or infrastructure through Harness can also create costs.
Is Kimi free?
Kimi provides a free allowance, but Agent, Deep Research, PPT, coding and other long tasks consume account credits. Paid memberships and extra-usage packs expand available capacity. Check the current signed-in account because plans and benefits change.
Which API is cheaper?
In the published USD examples above, DeepSeek Flash has lower input, cached-input and output token rates than Kimi K3 on the international Open Platform. That is a list-price comparison, not a quality-adjusted cost result. Include tools, cache writes, retries and human repair. The mainland China Kimi prices are a separate CNY schedule, not the international rate converted into another currency; compare the platform-specific price examples.
Which Kimi API endpoint should I use outside mainland China?
Kimi directs supported users outside mainland China to platform.kimi.ai and https://api.moonshot.ai/v1 for Chat Completions. The mainland China route uses platform.kimi.com and https://api.moonshot.cn/v1. Use a key issued for the same regional platform as the endpoint; accounts and balances are not shared. Check the regional API comparison before configuring a client.
Which has the longer context window?
Current DeepSeek Flash, DeepSeek Pro and Kimi K3 documentation all list one-million-token contexts. Kimi K2.7 Code and K2.6 currently list 256K. Headline context size does not establish reliable retrieval, usable output capacity or local memory requirements.
Can DeepSeek and Kimi run locally?
Official downloadable weights exist in both ecosystems, but current frontier models are extremely large. Local feasibility depends on the exact checkpoint, quantisation, runtime, context, hardware and licence. Downloading weights also does not recreate the complete hosted product.
Which is safer for confidential information?
There is no safe brand-level answer. DeepSeek consumer, Harness official models, Harness custom providers, Kimi regional consumer services, Kimi API, business products, Kimi Work and self-hosted models have different data flows. Kimi’s API-specific no-training statement should not be applied to consumer chats. Review the policy for the exact route and its technical architecture before using sensitive information.
Should I use both DeepSeek and Kimi?
Using both can be practical when roles are clear: DeepSeek for low-cost focused processing and Kimi for research or office-artifact workflows. Verify both with original sources, calculations, executable tests and human review rather than treating agreement between models as proof.
Sources checked
The original comparison was reviewed on October 8, 2026. The targeted October 15, 2026 update rechecked regional API access and authentication, published API price examples, related cache billing and the scope of Kimi privacy sources. It did not repeat a full product audit or run paid API requests.
Original comparison sources — October 8, 2026
- Official DeepSeek website and consumer download page.
- DeepSeek Harness product page, including current status, documented capabilities and official developer links.
- DeepSeek Harness Privacy Policy, last updated September 20, 2026.
- DeepSeek consumer Privacy Policy, last updated February 10, 2026.
- DeepSeek API documentation, current quickstart, change log and model guidance.
- DeepSeek API models and pricing.
- DeepSeek-V4.1-Flash release information.
- Official DeepSeek-V4.1-Flash model card.
- Official Kimi consumer product and Kimi Help Center.
- Kimi Work overview, including local-file workflows, plugins, Agent Swarm and long-horizon execution.
- Kimi Code overview and membership access guide.
- Kimi Code CLI quickstart documentation.
- Kimi Deep Research documentation.
- Kimi membership overview and current credit rules.
- Kimi mainland China API quickstart and model guidance.
- Kimi mainland China model-inference pricing and mainland China context-caching rules.
- Kimi consumer data-usage guidance published on kimi.com.
- Kimi API security guidance published on kimi.com.
- Official Kimi K3 technical overview and official Kimi K3 model card.
Sources rechecked for the regional update — October 15, 2026
- International Kimi API overview and mainland China API overview: protocol-specific base URLs.
- International quickstart, regional authentication and availability FAQ, and API error reference.
- DeepSeek model pricing, Kimi international inference-pricing page, and Kimi mainland China inference-pricing page.
- International caching guide and mainland China caching guide: regional input/cache rates, TTLs and usage accounting.
- International K3 announcement and Chinese K3 announcement: published output-price examples, not a substitute for the live regional price schedule.
- International search pricing and K3 quickstart: tool charges and the current search-readiness warning.
- kimi.ai Privacy Policy and kimi.com consumer data-usage guidance: distinct source scopes.
- International API data-security guidance and API data-security guidance on kimi.com.