DeepSeek
Chinese AI lab offering a free chat app, low-cost API, and MIT-licensed open-weight models
Editorial take
DeepSeek V4.1 Flash and V4 Pro are among the best-value models for coding and reasoning tasks. MIT-licensed and self-hostable, they cost a fraction of Western frontier model APIs. The main caveat is data privacy: the hosted API is operated in China, which rules it out for regulated industries.
What is DeepSeek?
DeepSeek is a Chinese AI lab that publishes open-weight large language models under the MIT license and runs a free chat app (web, iOS, Android) plus a low-cost API. The current API models are deepseek-flash (served by DeepSeek-V4.1-Flash-1017, released October 17, 2026) and deepseek-v4-pro, both with a 1M token context window and OpenAI- and Anthropic-compatible endpoints.
API prices are well below most Western frontier models, with peak-hour rates (weekday UTC mornings) at double the off-peak rate. The V4 family weights are on Hugging Face under the MIT license, so they can be self-hosted and fine-tuned, though the large mixture-of-experts models need substantial GPU hardware.
The main caveats are data privacy (the hosted service is operated in China, which raises concerns for regulated industries) and content moderation that differs from Western norms.
Best for
Cost-sensitive developers and researchers who want strong models at low API cost or self-hosted
Key strength
MIT-licensed open-weight models with very low API prices
Score breakdown (out of 5)
What you would use it for
- →Using a capable coding model at significantly lower API cost than OpenAI or Anthropic alternatives
- →Self-hosting a capable open-source model on your own infrastructure under the MIT license
- →Reasoning tasks using thinking mode with adjustable reasoning effort
- →Replacing more expensive API calls in existing OpenAI-compatible integrations via drop-in swap
- →Running local inference for privacy-sensitive development workflows via Ollama or LM Studio
Pros & Cons
👍 Pros
- ✓Among the cheapest API rates for frontier-level performance
- ✓Fully open-source - self-host with no ongoing licensing cost
- ✓1M token context window on both API models
- ✓OpenAI-compatible API works with existing integrations
👎 Cons
- ✗Operated in China - data privacy concerns for regulated industries
- ✗Content moderation differs from Western models on sensitive topics
- ✗Self-hosting requires substantial GPU hardware
- ✗API reliability can vary during peak demand
Key Features
- ✓ deepseek-flash (V4.1 Flash): fast low-cost model for code and writing
- ✓ deepseek-v4-pro: higher-capability model with optional thinking mode
- ✓ Open-source MIT license - self-hostable
- ✓ OpenAI-compatible API - drop-in replacement
- ✓ Works as a backend in Claude Code, Codex, OpenCode, LM Studio, and other tools
- ✓ Significantly cheaper API rates than Western frontier models
Available on
Integrates with
DeepSeek Pricing
✅ DeepSeek has a free plan - no credit card required to start.
Free (Chat)
- ✓DeepSeek V4.1 Flash via web and mobile apps
- ✓No credit card required
- ✓Rate limits apply
- ✓Official pricing page is a client-rendered SPA that would not load via fetch; model names confirmed on api-docs.deepseek.com, prices taken f
API (Pay-per-token)
- ✓deepseek-flash: $0.15/1M input (cache miss), $0.003 cache hit, $0.60/1M output (off-peak)
- ✓deepseek-v4-pro: $0.66/1M input (cache miss), $0.022 cache hit, $1.98/1M output (off-peak)
- ✓Peak hours (weekdays 01:00-04:00 and 06:00-10:00 UTC) cost 2x
- ✓1M token context window
- ✓OpenAI- and Anthropic-compatible API
- ✓Official pricing page is a client-rendered SPA that would not load via fetch; model names confirmed on api-docs.deepseek.com, prices taken f
Self-hosted
- ✓V4 Flash and V4 Pro weights on Hugging Face
- ✓MIT license - commercial use allowed
- ✓Requires significant GPU hardware
- ✓Official pricing page is a client-rendered SPA that would not load via fetch; model names confirmed on api-docs.deepseek.com, prices taken f
Video Review
DeepSeek vs Competitors
Latest news
From the blog
Five open-weight AI models in three days. StepFun beats Meta, and none beat the closed frontier.
Meta's Muse Spark Open, Reflection's Beam, StepFun's Step 5 Preview, NVIDIA's Nemotron 3.5 and a DeepSeek update all shipped downloadable weights this week. How they compare on size, license, price and independent scores, and when open weights are worth it.
Oct 16, 2026
Mistral ships le Chonk, a 1T open model. Europe has a contender, not a leader.
Mistral Large 4 is a trillion-parameter Mixture-of-Experts model with open weights promised for late October and a low API price. Independent tests rank it the strongest model built outside the US and China, and still far behind the closed frontier.
Oct 6, 2026
Researchers extract hidden reasoning from LLM APIs. Proprietary model internals are leaking.
Security research reveals methods to extract internal reasoning traces and model capabilities from proprietary LLM APIs, raising concerns about intellectual property theft and prompt injection vulnerabilities.
Aug 17, 2026
Developer resources
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