DeepSeek Coder delivers frontier-class software intelligence - free, open-source, and relentlessly advancing. From code generation to full-repo understanding, competition math to agentic workflows.
Three coding-optimized models covering speed, depth, and specialized code intelligence - all open-source under MIT license.
The most powerful open-source coding model. 1.6T parameter MoE, 49B active per token. Codeforces #1 at 3206 — beating GPT-5.4 (3168). 80.6% SWE-bench Verified. Terminal-Bench #1 at 67.9%. The definitive choice for complex software engineering.
Fast, cost-efficient coding intelligence. 284B MoE, 13B active. 79.0% SWE-bench — just 1.6 points behind Pro at 12.4× lower cost. 83 tok/s output. The default for high-volume coding pipelines, code review bots, and agentic systems where speed matters.
Purpose-built code model. 236B MoE (21B active), 128K context, pre-trained on 6T tokens including 2T+ code tokens. 82.6% HumanEval — GPT-4-Turbo level code generation. Supports 338 programming languages. The FIM (Fill-In-Middle) specialist for IDE integrations and code completion.
Rigorous benchmarks vs GPT-5.4, Claude Opus 4.6, and Gemini 3.1 Pro — with honest gaps noted. Data from DeepSeek model card, Artificial Analysis, and BenchLM.
Not a toy. Not just autocomplete. DeepSeek Coder understands entire repositories, debugs at depth, and operates as an autonomous software agent.
Generate complete, production-quality code from natural language specs. Understands architecture, dependencies, and coding conventions for clean, idiomatic output.
340+ languagesProcess entire codebases with 1M token context. Understands file relationships, imports, class hierarchies, and cross-file dependencies — not just snippets.
1M tokensTrace errors through stack frames, understand side effects, and identify root causes across multiple files. Explains why the bug exists, not just where.
Root causePredict missing code from both prefix and suffix context. Powers IDE code completion with PSM (Prefix-Suffix-Middle) mode. Works with Cursor, VS Code, and JetBrains plugins.
IDE readySecurity vulnerabilities, performance bottlenecks, code quality issues, and compliance risks — all in a single structured review with severity levels and actionable fixes.
Security + perfSafely refactor legacy code, migrate between frameworks, modernize APIs, and decompose monoliths — with full understanding of downstream effects across the codebase.
Safe migrationGenerate comprehensive test suites — unit, integration, and edge cases. Understands the semantics of what the code should do, not just what it does, producing meaningful test coverage.
Full coverageV4-Pro powers autonomous dev agents — plan, code, test, and deploy across multi-file projects. Terminal-Bench #1 for CLI and systems tool use.
Agent nativeOlympiad-level problem solving, optimization algorithms, numerical methods, and formal proof assistance. 97.3% MATH-500. IMO 2025 Gold Medal.
IMO GoldPython, JavaScript, TypeScript, Java, C, C++, C#, Rust, Go, Swift, Kotlin, Ruby, PHP, Scala, R, MATLAB, SQL, Shell, and 320+ more. Strong support for all major frameworks.
All stacksFull model weights on Hugging Face under MIT License. Self-host, fine-tune on your codebase, and deploy commercially — zero restrictions, zero royalties.
Commercial ✓Change 2 lines of code — base_url and api_key — to migrate from GPT. All existing streaming, function calling, and structured output code works unchanged.
2-line migrationDeepSeek uses the OpenAI API format. Change two lines — base URL and API key. Everything else stays identical.
deepseek-chat and deepseek-reasoner retire. Update to deepseek-v4-flash or deepseek-v4-pro before that date.
DeepSeek Coder powers developer tools, AI coding agents, and enterprise automation across every software engineering domain.
Build IDE plugins and inline coding assistants with FIM (Fill-In-Middle) support. Power autocomplete, inline suggestions, and real-time debugging in VS Code, Cursor, JetBrains.
Build PR review bots that check security, performance, and best practices on every commit. V4-Flash at 83 tok/s handles high-volume pipelines with a sub-second PR review.
Modernize Python 2 → 3, jQuery → React, Django → FastAPI migrations. 1M context processes entire monoliths in a single pass. V4-Pro understands architectural intent, not just syntax.
Auto-generate unit, integration, and property-based tests. Understands what code should do (not just what it does), producing meaningful edge-case coverage that actually catches bugs.
Deploy autonomous agents that plan, code, test, and deploy across multi-file projects. V4-Pro's Terminal-Bench #1 score means reliable tool use in CI/CD pipelines and DevOps workflows.
Generate API docs, inline comments, README files, and architecture decision records from existing codebases. Understands code intent and produces documentation developers actually want to read.
Solve competitive programming problems, design efficient algorithms, and implement complex data structures. Codeforces #1 at 3206 — better than every human competitor except the absolute elite.
Write, optimize, and explain complex SQL queries. Design schemas, analyze query plans, and generate migration scripts. Understands PostgreSQL, MySQL, SQLite, BigQuery, and more.
Identify OWASP Top 10 vulnerabilities, SQL injection, XSS, CSRF, and dependency risks. V4-Pro reviews code with the eye of a senior security engineer — severity-ranked, with fixes.
From zero to AI-powered code in under 5 minutes — web chat, API, or self-hosted.
Use chat.deepseek.com free web chat (Expert Mode = V4-Pro), download the iOS/Android app, or get an API key at platform.deepseek.com.
Use deepseek-v4-flash for speed & cost. deepseek-v4-pro for complex tasks. Enable Think Max for hard algorithms and multi-step engineering.
Specify language, framework, constraints, and output format. Use XML tags for context and code. The more precise your spec, the better the output.
Install pip install openai. Set base_url="https://api.deepseek.com/v1". Use deepseek-v4-pro or deepseek-v4-flash. That's it — fully compatible.
Download weights from Hugging Face under MIT License. Use Ollama for local distilled models, or vLLM / SGLang for full model inference on GPU servers.
Cache hits save 90% on input costs. Keep system prompts stable at the top. Variable content goes at the end. $0.014/1M vs $0.14/1M at scale.
Pay-as-you-go API. No monthly subscription. The web chat is completely free — always.
Full access to V4-Pro (Expert Mode) and V4-Flash (Instant Mode) in the chat interface. No limits for personal use.
High-volume coding pipelines. 79% SWE-bench at 12.4× lower cost than Pro. 83 tok/s streaming.
Flagship intelligence for complex coding. 80.6% SWE-bench. Codeforces #1. 7× cheaper than Claude Opus per output token.
Download weights from Hugging Face. MIT License — commercial use free, no royalties. Fine-tune on your own codebase.
💡 No monthly fees. Cache hits save 90% on repeated system prompts. New accounts receive $5 in free API credits.
On specific coding benchmarks, yes. V4-Pro has the highest Codeforces rating of any AI model ever tested (3206 vs GPT-5.4's 3168), the top LiveCodeBench score (93.5), and ties Claude Opus 4.6 on SWE-bench Verified (80.6% vs 80.8%). However, "better" depends on the task. Claude may retain an edge on nuanced reasoning with ambiguity, and Gemini on factual recall. For pure code generation, competitive programming, and systems tasks, V4-Pro is the best open-source option — and competitive with the best proprietary models at 7× lower cost.
DeepSeek-Coder V2 is a dedicated coding model released June 2024. It's a 236B MoE model (21B active) specialized for code with 338 language support, 128K context, and 82.6% HumanEval. It excels at IDE-style FIM (Fill-In-Middle) code completion tasks. The newer V4-Pro and V4-Flash (April 2026) are general-purpose models with much stronger coding performance — V4-Pro hits 80.6% SWE-bench (Coder V2 doesn't report SWE-bench) and scores Codeforces #1. For new projects, V4 models are recommended. Coder V2 remains useful for FIM-specialized IDE integration workflows where the smaller active parameter count is beneficial.
Several options: (1) The Continue.dev extension supports DeepSeek via API — set base URL to https://api.deepseek.com/v1 and model to deepseek-v4-flash. (2) Cursor IDE supports custom model endpoints — add DeepSeek in Models settings. (3) Cline (VS Code extension) supports DeepSeek directly. (4) For local FIM code completion, run DeepSeek-Coder V2 via Ollama (ollama run deepseek-coder-v2) and point your IDE at http://localhost:11434. V4-Flash's 83 tok/s makes it fast enough for real-time autocomplete via API.
DeepSeek-Coder V2 supports 338 programming languages — expanded from 86 in the original Coder model. V4-Pro and V4-Flash support this range and more. All major languages are included: Python, JavaScript, TypeScript, Java, C, C++, C#, Rust, Go, Swift, Kotlin, Ruby, PHP, Scala, R, MATLAB, SQL, Shell (bash/zsh), Dockerfile, YAML, and 310+ more. Strong performance on Python, Java, C++ particularly, matching GPT-4-Turbo level on HumanEval.
Yes. All DeepSeek models are MIT licensed — you can fine-tune and deploy commercially with no restrictions or royalties. Download base model weights from huggingface.co/deepseek-ai. For V4-Flash fine-tuning: 160 GB weights (FP8), recommend 4×H200 or 2×A100 80GB setup for full fine-tuning. For more accessible fine-tuning, the V2-16B and distilled R1 variants run on single consumer-grade GPUs. Use standard PEFT/LoRA techniques — the model is compatible with Hugging Face transformers and SFTTrainer.
For most everyday coding tasks, Flash is functionally equivalent to Pro. The key differences: SWE-bench 79.0% (Flash) vs 80.6% (Pro) — a 1.6 point gap. LiveCodeBench 91.6 vs 93.5. Terminal-Bench (agentic CLI) 56.9% vs 67.9% — this is the biggest gap. For routine code generation, review, debugging, and refactoring: start with Flash (12.4× cheaper). For complex multi-step agentic workflows, competitive algorithm problems, or when you need the best possible code quality: use Pro. Benchmark your specific workload before committing.
Yes. V4-Pro and V4-Flash support OpenAI-compatible function calling (tool use) with the same JSON schema format. JSON mode ("response_format": {"type": "json_object"}) forces structured output. All existing OpenAI function-calling integrations work without modification — just change the base URL and API key. DeepSeek V4 also introduces an improved agentic task synthesis pipeline that significantly improves tool-use accuracy for building autonomous coding agents.
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