DeepSeek: Most Powerful Open-Source AI

💰 Extremely Low Cost

API pricing is 1/10 of GPT-4. Even enterprise apps can afford it easily.

🎯 Exceptional Performance

Excels in code generation, math reasoning, long document understanding. Surpasses GPT-3.5 in multiple benchmarks.

🔓 Fully Open Source

Model weights and technical reports fully public. Can be deployed locally for data security.

🚀 Continuous Evolution

V1 to V4 continuous iteration. Each update brings performance leap.

DeepSeek-V3 (Dec 2024)

671B total params, 37B active. MoE architecture achieves low-cost high-performance. Trained on 14.8T tokens, cost only 2.788M H800 GPU hours, stable training with no rollbacks.

DeepSeek-V2 (May 2024)

236B total params, 21B active, supports 128K context. Training cost reduced 42.5%, KV cache reduced 93.3%, throughput improved 5.76x.

DeepSeek-Coder-V2 (Jun 2024)

Code specialist, supports 338 programming languages, 128K ultra-long context, industry-leading code completion and generation.

DeepSeek-VL (Mar 2024)

Open-source vision-language model, supports 1024×1024 high-res image understanding, excellent multimodal performance.

💻 Code Development

Code generation, bug fixes, code explanation, unit test writing. 10x productivity boost.

📚 Document Understanding

Long document summarization, contract review, paper analysis. 128K context handles easily.

🎓 Education Tutoring

Math problem solving, Q&A, concept explanation. AI tutor assistant.

✍️ Content Creation

Article writing, marketing copy, multilingual translation. Boost content output.

Register Account

Sign up on Atlas Cloud, no credit card required. Complete registration in 1 minute and get free credits.

Get API Key

Log into console, create API key with one click. Supports multiple key management for different projects.

Start Calling

Copy sample code, replace API key and start using. Compatible with OpenAI format, zero migration cost.

What is DeepSeek?

DeepSeek is an open-source large language model developed by Chinese company DeepSeek AI. Performance matches ChatGPT but cost is only 1/10. Supports code generation, document understanding, math reasoning. Fully open-source and can be deployed locally.

Is DeepSeek free?

Yes! DeepSeek provides free API quota. Individual developers can use directly. Enterprise users can choose paid version for higher quota. Register on Atlas Cloud to get free trial credits.

Is DeepSeek better than ChatGPT?

DeepSeek approaches or surpasses GPT-3.5 in code generation and math reasoning, and matches GPT-4 in some tasks. Main advantages: low cost and fully open-source. Enterprises can deploy locally to protect data security.

Is DeepSeek safe?

DeepSeek is developed by a legitimate company with fully public code. Enterprise users can choose local deployment, data stays on-premise. However, any AI has potential risks. Recommended to use enterprise version on Atlas Cloud with professional security guarantees.

How to use DeepSeek?

Three ways: 1) Online trial - Atlas Cloud provides free trial; 2) API calls - Integrate into your apps; 3) Local deployment - Download model weights to your server. Beginners recommended to try on Atlas Cloud first.

When will DeepSeek V4 be released?

DeepSeek V4 is expected to launch in March 2026. TechNode reported on March 2 that the release is imminent. V4 will be a trillion-parameter native multimodal model with 1M+ token context, at pricing 10-25x cheaper than GPT-5.4. Subscribe for launch notifications.

What are DeepSeek V4 new features?

DeepSeek V4 key features: 1) Native multimodal — text, image, video, audio processing; 2) 1 trillion parameters total, 32B active per token; 3) 1 million+ token context window; 4) API pricing $0.10-$0.30/M tokens (10-25x cheaper than GPT-5.4); 5) Open-source and free to self-host. V4 targets 80%+ on SWE-bench coding benchmarks.

What languages does DeepSeek support?

DeepSeek supports Chinese, English and multiple languages. DeepSeek-Coder-V2 specifically for code tasks, supports 338 programming languages, a powerful assistant for developers.

Can DeepSeek generate images?

DeepSeek V3 is primarily a text model. However, DeepSeek V4 (launching March 2026) will be natively multimodal, supporting text, image, video and audio processing. DeepSeek-VL can already understand image content. For current image generation, use Stable Diffusion or DALL-E.

Is DeepSeek open source?

Yes, DeepSeek is fully open source! Model weights, training code, technical reports are all public on GitHub. Enterprises can freely download and deploy without vendor lock-in concerns.

How to download DeepSeek?

Visit DeepSeek GitHub repo or HuggingFace model library to download. Note: model is large (tens of GB), requires high-end GPU to run. Recommend trying on Atlas Cloud first, confirm needs before local deployment.

How long context does DeepSeek support?

DeepSeek-V2/V3 supports 128K token context, about 100K characters. DeepSeek V4 (March 2026) will support 1 million+ tokens — enough to process entire books, full codebases, or thousands of pages of documents in a single query.

What is Atlas Cloud?

Atlas Cloud is a leading AI model service platform and OpenRouter ecosystem partner. Provides enterprise-grade access to DeepSeek and open-source models, with new models available on release day. Passed SOC I & II, HIPAA international certifications, meets enterprise security compliance requirements. Provides: 1) Ready-to-use API; 2) 99.9% SLA guarantee; 3) Multi-region deployment; 4) Technical support. New users get free credits upon registration.

Who is DeepSeek suitable for?

Individual developers: low-cost AI assistant; Enterprises: local deployment protects data; Students: free AI learning tool; Researchers: open-source customizable. Basically suitable for all scenarios needing AI!

What are DeepSeek limitations?

Free version has request rate limits. Local deployment needs high-end GPU (at least 24GB VRAM). Some sensitive topics may be refused. Using on Atlas Cloud solves most limitation issues.

What is Engram Memory in DeepSeek V4?

Engram Memory is a revolutionary conditional memory mechanism in V4 that enables effectively infinite context. It retrieves memories in O(1) time, allowing the model to instantly recall your entire codebase or knowledge base without the latency of traditional KV Cache approaches.

Can I run DeepSeek V4 locally?

Yes. Quantized versions (4-bit/8-bit) are designed for consumer hardware. The 67B active version needs ~24GB VRAM (e.g., RTX 4090). The full 1T MoE model requires enterprise clusters. Optimized GGUF versions will support Apple Silicon Macs with 64GB+ unified memory.

Does DeepSeek V4 run on Apple Silicon (Mac M3/M4)?

Yes. Optimized GGUF versions are expected for Mac Studio/Pro with 64GB+ unified memory. Apple's Metal Performance Shaders provide GPU acceleration for efficient local inference on M3/M4 chips.

Can I use DeepSeek with VS Code or Cursor?

Yes. DeepSeek is fully compatible with Cursor, Continue.dev, Cline, and other AI coding assistants via API key. Simply set the DeepSeek API endpoint and key in your IDE settings. Compatible with OpenAI API format.

DeepSeek V4 vs GPT-5.4: Which is better?

DeepSeek V4 targets 80%+ SWE-bench (vs GPT-5.4's 77.2%) at $0.10-$0.30/M tokens (vs GPT-5.4's $2.50-$15/M). That's 10-25x cheaper with potentially better coding performance. Plus V4 is open-source with free self-hosting — GPT-5.4 is closed-source API-only.

DeepSeek V4 vs Claude 4.6: Which is better for coding?

Claude Opus 4.6 scores 80.8% on SWE-bench at $5/$25 per M tokens. DeepSeek V4 targets 80%+ at $0.10-$0.30/M — potentially 15-80x cheaper. Claude excels in long-context reliability, but V4's Engram Memory offers effectively infinite context. Key advantage: V4 is open-source.

DeepSeek V4 vs Gemini 3.1 Pro: How do they compare?

Gemini 3.1 Pro scores 80.6% on SWE-bench at $2/$12 per M tokens with native multimodal support. DeepSeek V4 offers similar capabilities (native multimodal, 1M+ context, 80%+ SWE-bench target) at 10-20x lower cost, plus open-source weights for self-hosting.

Can DeepSeek V4 fix bugs across an entire repository?

Yes. V4's massive context window and Engram Memory allow it to analyze full codebases for repo-level bug fixing. It can understand cross-file dependencies, trace bug origins, and generate fixes that consider the entire project structure.

Does DeepSeek V4 support Python, Rust, and other languages?

V4 is SOTA for Python, Rust, C++, JavaScript, TypeScript, Go, and 50+ other languages. Trained on a massive specialized code corpus, it excels at code generation, debugging, refactoring, and test writing across all major programming languages.

Is user data used for training by DeepSeek?

API data is NOT used for training by default. Web chat data may be used unless you opt out in settings. For maximum privacy, self-host V4 locally using the open-source weights — your data never leaves your servers.

What is DeepSeek Sparse Attention (DSA)?

DSA is a novel attention mechanism in V4 that reduces computational costs by ~50% while supporting 1M+ token context windows. Combined with FP8 mixed precision inference, it delivers frontier performance at a fraction of the compute cost.