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DeepSeek vs Kimi – 深度求索与 Kimi 全面对比

DeepSeek vs Kimi head-to-head: reasoning, long context, web search, API pricing and free tiers — with a buying guide深度推理、长文本、联网搜索、API 价格与免费额度全面对比,附选型建议

DeepSeek Official Site ↗ DeepSeek 官网 ↗ Kimi Official Site ↗ Kimi 官网 ↗ ⚖️ Compare
Category分类
Comparison · LLM对比 · 大语言模型
comparison
Players对阵双方
DeepSeek vs Kimi
DeepSeek (Hangzhou) vs Moonshot AI深度求索 vs 月之暗面
Price价格
Both free to chat对话均免费
API: DeepSeek much cheaperAPI:DeepSeek 便宜得多
Tags标签
comparison, llm, deepseek, kimi, chinese
5 tags total个标签

One-line verdict: pick DeepSeek for reasoning, code, and cheap API calls; pick Kimi for long-document reading and research. They are complementary, not substitutes — most power users keep both. If you can only keep one account, DeepSeek's open weights and ultra-low API price make it the safer default.

一句话结论:做推理、写代码、高频调用 API 选 DeepSeek;啃长文档、做调研选 Kimi。两者互补而非替代,重度用户建议两个都留。如果只能留一个,DeepSeek 的开源权重和超低 API 价格让它成为更稳妥的默认选项。

— 中国吧 AI Tools Hub Editorial Team

Why Compare DeepSeek and Kimi?为什么要对比 DeepSeek 和 Kimi?

DeepSeek (Hangzhou DeepSeek, 深度求索) broke out with open-weight models V3 and the reasoning model R1, and its V3.2 iteration ranks among the strongest models of 2026. It is famous for frontier-level reasoning at a fraction of competitors' prices.DeepSeek(杭州深度求索)凭借开源模型 V3 和推理模型 R1 出圈,2026 年的 V3.2 版本综合表现位列当年第一梯队。它以远低于同行的成本提供顶尖推理能力而闻名。

Kimi, from Beijing's Moonshot AI (月之暗面), made its name as the long-context king — it can swallow whole books or dozens of PDFs in one go. The newer K2 series shifted toward stronger reasoning and agentic tool use.Kimi 出自北京月之暗面,靠"长文本之王"打响名号——一次能吞下整本书或几十份 PDF。新一代 K2 系列 转向更强的推理和 Agent 工具调用能力。

Both are free to chat in China with no special network setup, and both are open to developers via API. They overlap a lot, but their strengths point in different directions — this page lays them out side by side.两者在国内都能直接免费对话,也都开放 API 给开发者。它们重叠度很高,但强项各有侧重——本页把它们放在一起逐项对比。

Head-to-Head Spec Table核心参数对比表

Dimension对比维度 DeepSeek Kimi
Latest flagship model最新旗舰模型 V3.2 (chat) / R1 (reasoning)V3.2(对话)/ R1(推理) K2 series (agentic, tool-calling)K2 系列(Agent、工具调用)
Reasoning / math / code推理 / 数学 / 代码 ⭐⭐⭐⭐⭐ top-tier among free models免费档顶尖水平 ⭐⭐⭐⭐ strong, K2 improved a lot较强,K2 进步明显
Long-context window长文本上限 ~128K tokens约 128K tokens ⭐ million-token class, can ingest whole books百万级上下文,可吞整本书
Web search联网搜索 ✅ yes支持 ✅ yes, with cited sources支持,带引用来源
Multimodal (image/video)多模态(图像/视频) weak — no built-in image/video generation较弱,暂无内置生图/生视频 weak — file/PDF parsing is the strength较弱,强项是文件/PDF 解析
Free chat免费对话 free (web + app)免费(网页/App) free (web + app), limits on advanced models免费(网页/App),高阶模型有限制
API pricingAPI 价格 ⭐ very low, tiered cache-hit pricing极低,缓存命中分档计价 mid-range, see official site中等档位,以官网为准
Open weights开源权重 ✅ MIT — self-host via OllamaMIT 协议,可本地部署 not open未开源
Chinese optimization中文优化 ⭐⭐⭐⭐⭐ excellent优秀 ⭐⭐⭐⭐⭐ excellent, especially long Chinese docs优秀,中文长文档尤其强
Access in China国内访问 direct, no VPN needed直连,无需特殊网络 direct, no VPN needed直连,无需特殊网络
💡 Model versions, context limits, and prices change frequently — the official site is authoritative. Figures above reflect public sources as of 2026-10.模型版本、上下文上限和价格变化频繁,具体以官网为准。以上为截至 2026-10 的公开信息。

Pros & Cons各自优缺点

DeepSeek

✓ Pros优点

  • Top-tier reasoning (R1) among free models — math, code, logic免费模型中顶尖的推理能力(R1),数学、代码、逻辑强
  • Open weights (MIT) — self-host via Ollama, fine-tune freely权重开源(MIT),可本地部署、自由微调
  • Very low API prices with cache-hit tiers — best for high-volume useAPI 价格极低且有缓存命中分档,适合高频调用

✕ Cons缺点

  • No built-in image or video generation暂无图像、视频等多模态生成功能
  • Service can be slow or busy during peak hours高峰期服务可能繁忙、响应变慢

Kimi

✓ Pros优点

  • Million-token-class context — whole books or dozens of PDFs in one go百万级上下文,一次可吞整本书或几十份 PDF
  • Strong at long Chinese document comprehension, summarization, and cross-comparison中文长文档理解、摘要、交叉比对能力强
  • Web search with cited sources — good for research workflows联网搜索带引用来源,适合做调研

✕ Cons缺点

  • Weights not open — no self-hosting option权重未开源,无法本地部署
  • API pricing is mid-range; weaker at deep reasoning than R1API 价格属中等档位;深度推理不如 R1

Who Should Pick Which?选型建议:分人群看

🎓 Students学生

  • Kimi for theses and literature: dump whole papers in and ask targeted questionsKimi 写论文、读文献:整篇论文丢进去定向提问
  • DeepSeek for math, physics, and code homework with step-by-step reasoningDeepSeek 做数理化和代码作业,分步推理讲解

💻 Developers开发者

  • DeepSeek for API batch jobs: the cheapest capable API on the market, OpenAI-compatibleDeepSeek 做 API 批量任务:市面上最便宜的可用 API,兼容 OpenAI 格式
  • Kimi for long-codebase or long-spec comprehension with its large contextKimi 理解超长代码库或需求文档,靠大上下文

🏢 Enterprises企业

  • DeepSeek for cost-sensitive RAG/chatbot builds; open weights allow private deploymentDeepSeek 做成本敏感的 RAG/客服机器人;开源权重支持私有化部署
  • Kimi for contract review, compliance, and consulting research over long documentsKimi 做合同审查、合规与咨询调研,长文档分析是独门能力

Related AI Tools相关 AI 工具

Other tools mentioned in this comparison:本对比中提到的其他工具:

Frequently Asked Questions常见问题

Which is better for long documents, DeepSeek or Kimi?读长文档选 DeepSeek 还是 Kimi? ▼
Kimi is the better pick for long documents: its long-context window is much larger, making it ideal for contracts, theses, and research reports. DeepSeek handles regular-length documents well but its context window is smaller.选 Kimi:它的上下文窗口大得多,适合合同、论文、研报这类长文档。DeepSeek 处理常规长度文档没问题,但上下文上限较小。
Which has cheaper API pricing, DeepSeek or Kimi?API 谁更便宜,DeepSeek 还是 Kimi? ▼
DeepSeek's API is significantly cheaper, with tiered cache-hit pricing on the official platform, making it the budget choice for high-volume developers. Kimi's API is priced higher per million tokens. Check both official sites for current rates.DeepSeek 的 API 便宜得多,官网有缓存命中分档计价,是高频调用开发者的预算首选。Kimi 的 API 单价更高。具体价格以双方官网为准。
Are DeepSeek and Kimi free to use?DeepSeek 和 Kimi 免费吗? ▼
Both offer free web and app chat. DeepSeek's chat is fully free, and its API is very cheap pay-as-you-go. Kimi is also free for daily use with some limits on advanced models and high-frequency calls.两者网页/App 对话都免费。DeepSeek 对话完全免费,API 按量计费非常便宜。Kimi 日常使用也免费,高阶模型和高频调用有一定限制。
Which is stronger at math and code reasoning?数学和代码推理谁更强? ▼
DeepSeek-R1 is stronger at math, code debugging, and step-by-step reasoning among free models. Kimi's K2 series has improved agentic and tool-calling ability, but DeepSeek still leads on pure reasoning benchmarks.DeepSeek-R1 更强,在免费模型里数学、代码调试和分步推理都是第一梯队。Kimi 的 K2 系列在 Agent 和工具调用上进步明显,但纯推理跑分仍是 DeepSeek 领先。
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