Codeforces #1 — Rating 3206, beating GPT-5.4 (3168) & Gemini (3052) LiveCodeBench — 93.5 Pass@1, highest of any model SWE-bench Verified — 80.6%, within 0.2pt of Claude Opus 4.6 340+ Languages — Python, Java, C++, Rust, Go, TypeScript and more 1M Token Context — Process entire codebases in a single request MIT License — Self-host, fine-tune, commercial use — no restrictions Codeforces #1 — Rating 3206, beating GPT-5.4 (3168) & Gemini (3052) LiveCodeBench — 93.5 Pass@1, highest of any model SWE-bench Verified — 80.6%, within 0.2pt of Claude Opus 4.6 340+ Languages — Python, Java, C++, Rust, Go, TypeScript and more 1M Token Context — Process entire codebases in a single request MIT License — Self-host, fine-tune, commercial use — no restrictions
V4-Pro scores Codeforces #1 · 93.5 LiveCodeBench · MIT Open Source

The Best Open-Source
AI Coder.

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.

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3206Codeforces #1
93.5LiveCodeBench
80.6%SWE-bench
340+Languages
1MContext tokens
MITLicense
Model Family

Every Model, Every Coding Task

Three coding-optimized models covering speed, depth, and specialized code intelligence - all open-source under MIT license.

⭐ #1 Open-Source Coder
🔥 V4 · FLAGSHIP 🧠
DeepSeek-V4-Pro
deepseek-v4-pro · Released April 24, 2026

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.

1.6T
Parameters
80.6%
SWE-bench
93.5
LiveCodeBench
1M
Context
Try Expert Mode Free →
⚡ V4 · FAST 💨
DeepSeek-V4-Flash
deepseek-v4-flash · Released April 24, 2026

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.

284B
Parameters
79.0%
SWE-bench
83
tok/s
$0.14
per 1M in
Get API Key →
💻 SPECIALIZED ⌨️
DeepSeek-Coder V2
deepseek-coder-v2 · Released June 17, 2024

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.

236B
Parameters
82.6%
HumanEval
338
Languages
128K
Context
Hugging Face ↗
Performance Benchmarks

How DeepSeek Coder Stacks Up

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.

SWE-bench Verified
Real GitHub issue resolution · Pro-Max mode
DS V4-Pro ≈ Claude80.6%
V4-Pro
80.6%
Claude Op. 4.6
80.8%
Gemini 3.1 Pro
80.6%
GPT-5.4
72.0%
LiveCodeBench Pass@1
Live competitive programming
DeepSeek #1 · 93.5
V4-Pro
93.5
V4-Flash
91.6
Gemini 3.1 Pro
91.7
Claude Op. 4.6
88.8
Terminal-Bench 2.0
Agentic CLI and systems programming
DeepSeek #1 · 67.9%
V4-Pro
67.9%
Gemini 3.1 Pro
68.5%
Claude Op. 4.6
65.4%
V4-Flash
56.9%
Codeforces Rating (ELO)
Competitive programming — highest score ever recorded
DeepSeek #1 · 3206
V4-Pro
3206
GPT-5.4
3168
Gemini 3.1 Pro
3052
HumanEval (Coder V2)
Code generation from natural language — GPT-4-Turbo level
Coder V2: 82.6%
V4-Pro
90.2%
Coder V2 (236B)
82.6%
GPT-4-Turbo
87.1%
Coder V2 Lite (16B)
65.2%
BenchLM Open-Weight Coding Score
Composite score across SWE-bench, LiveCodeBench, and others
Best open-weight · 88
V4-Pro (Max)
88 / 100
MATH-500
Mathematical reasoning — V4-Pro with Think Max
V4-Pro 97.3%
V4-Pro (Think)
97.3%
GPT-5.4
96.4%
Coder V2 Instruct
75.7%
MMLU-Pro (General Knowledge)
Multi-discipline knowledge
V4-Pro
73.5%
GPT-5.4
~75%
Coding Features

Built for Real Software Engineering

Not a toy. Not just autocomplete. DeepSeek Coder understands entire repositories, debugs at depth, and operates as an autonomous software agent.

📝
Code Generation

Generate complete, production-quality code from natural language specs. Understands architecture, dependencies, and coding conventions for clean, idiomatic output.

340+ languages
🔍
Repository Understanding

Process entire codebases with 1M token context. Understands file relationships, imports, class hierarchies, and cross-file dependencies — not just snippets.

1M tokens
🐛
Deep Debugging

Trace errors through stack frames, understand side effects, and identify root causes across multiple files. Explains why the bug exists, not just where.

Root cause
🔄
Fill-In-Middle (FIM)

Predict 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 ready
👁️
Code Review

Security vulnerabilities, performance bottlenecks, code quality issues, and compliance risks — all in a single structured review with severity levels and actionable fixes.

Security + perf
🔀
Refactoring

Safely refactor legacy code, migrate between frameworks, modernize APIs, and decompose monoliths — with full understanding of downstream effects across the codebase.

Safe migration
🧪
Test Generation

Generate 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 coverage
🤖
Agentic Workflows

V4-Pro powers autonomous dev agents — plan, code, test, and deploy across multi-file projects. Terminal-Bench #1 for CLI and systems tool use.

Agent native
📐
Algorithm & Math

Olympiad-level problem solving, optimization algorithms, numerical methods, and formal proof assistance. 97.3% MATH-500. IMO 2025 Gold Medal.

IMO Gold
🌐
340+ Languages

Python, 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 stacks
🔓
MIT Open Source

Full model weights on Hugging Face under MIT License. Self-host, fine-tune on your codebase, and deploy commercially — zero restrictions, zero royalties.

Commercial ✓
🔌
OpenAI API Compatible

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 migration
Code Examples

Integrate in Minutes

DeepSeek uses the OpenAI API format. Change two lines — base URL and API key. Everything else stays identical.

deepseek-coder · OpenAI-compatible API
# pip install openai — uses OpenAI SDK, no new packages from openai import OpenAI import os # Two-line migration from GPT — only these two change client = OpenAI( api_key=os.getenv("DEEPSEEK_API_KEY"), base_url="https://api.deepseek.com/v1" ) response = client.chat.completions.create( model="deepseek-v4-pro", # or deepseek-v4-flash messages=[ {"role": "system", "content": "You are an expert software engineer."}, {"role": "user", "content": "Write a binary search in Python with type hints."} ], max_tokens=2048, stream=True # 83 tok/s on V4-Flash ) for chunk in response: if chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True)
// npm install openai — no extra packages import OpenAI from 'openai'; const client = new OpenAI({ apiKey: process.env.DEEPSEEK_API_KEY, baseURL: 'https://api.deepseek.com/v1', }); const stream = await client.chat.completions.create({ model: 'deepseek-v4-flash', // fast + cheap for most tasks messages: [{ role: 'user', content: 'Explain this TypeScript error and fix it: ...' }], stream: true, }); for await (const chunk of stream) { process.stdout.write(chunk.choices[0]?.delta?.content ?? ''); }
# Structured code review with severity levels from openai import OpenAI client = OpenAI( api_key="<your-key>", base_url="https://api.deepseek.com/v1" ) code = """ def process_payment(user_id, card_number, amount): query = f"INSERT INTO payments VALUES ({user_id}, {card_number}, {amount})" db.execute(query) """ review = client.chat.completions.create( model="deepseek-v4-pro", messages=[{ "role": "user", "content": f"""Review this code for: 1. Security vulnerabilities [CRITICAL/HIGH/MEDIUM/LOW] 2. Performance issues 3. Best practice violations Code: <code>{code}</code> Return: numbered issues with severity, description, and fixed code.""" }] ) print(review.choices[0].message.content)
# Coding agent with Think Max — for hard engineering problems from openai import OpenAI client = OpenAI( api_key="<your-key>", base_url="https://api.deepseek.com/v1" ) response = client.chat.completions.create( model="deepseek-v4-pro", messages=[{ "role": "user", "content": """Design a zero-downtime migration from PostgreSQL 12 to 15. Include: (1) pre-migration checklist, (2) dual-write strategy, (3) cutover steps, (4) rollback plan. Return as a production-ready runbook.""" }], max_tokens=32768, extra_body={ "thinking": { "type": "enabled", "budget": "max" # Think Max for complex engineering } } ) # reasoning_content = the full engineering analysis chain print(response.choices[0].message.content)
⚠️ July 24, 2026: Legacy model aliases deepseek-chat and deepseek-reasoner retire. Update to deepseek-v4-flash or deepseek-v4-pro before that date.
Use Cases

What Can You Build?

DeepSeek Coder powers developer tools, AI coding agents, and enterprise automation across every software engineering domain.

01
AI Coding Assistants

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.

02
Automated Code Review

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.

03
Legacy Code Migration

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.

04
Test Generation

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.

05
Software Engineering Agents

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.

06
Documentation Generation

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.

07
Algorithm Design

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.

08
Database & SQL

Write, optimize, and explain complex SQL queries. Design schemas, analyze query plans, and generate migration scripts. Understands PostgreSQL, MySQL, SQLite, BigQuery, and more.

09
Security Auditing

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.

Getting Started

How to Use DeepSeek Coder

From zero to AI-powered code in under 5 minutes — web chat, API, or self-hosted.

1
Choose access method

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.

2
Pick the right model

Use deepseek-v4-flash for speed & cost. deepseek-v4-pro for complex tasks. Enable Think Max for hard algorithms and multi-step engineering.

3
Write structured prompts

Specify language, framework, constraints, and output format. Use XML tags for context and code. The more precise your spec, the better the output.

4
Integrate via API

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.

5
Or self-host (open source)

Download weights from Hugging Face under MIT License. Use Ollama for local distilled models, or vLLM / SGLang for full model inference on GPU servers.

6
Optimize with caching

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.

Pricing

Up to 95% Cheaper Than GPT-5.5

Pay-as-you-go API. No monthly subscription. The web chat is completely free — always.

Free Forever
Web Chat
$0/month

Full access to V4-Pro (Expert Mode) and V4-Flash (Instant Mode) in the chat interface. No limits for personal use.

V4-Pro (Expert Mode)✓ Free
V4-Flash (Instant)✓ Free
DeepThink (Think Max)✓ Free
File / code uploads✓ Free
Start Coding Free →
Most Popular
V4-Flash API
$0.14/1M in

High-volume coding pipelines. 79% SWE-bench at 12.4× lower cost than Pro. 83 tok/s streaming.

Input (cache miss)$0.14/1M
Input (cache hit)$0.014/1M
Output$0.28/1M
Context1M tokens
Get API Key →
V4-Pro API
$1.74/1M in

Flagship intelligence for complex coding. 80.6% SWE-bench. Codeforces #1. 7× cheaper than Claude Opus per output token.

Input (cache miss)$1.74/1M
Input (cache hit)$0.174/1M
Output$3.48/1M
vs Claude Opus7× cheaper out
Get API Key →
Self-Host (MIT)
Open Source

Download weights from Hugging Face. MIT License — commercial use free, no royalties. Fine-tune on your own codebase.

API fees$0 forever
V4-Flash weights160 GB (FP8)
Min GPU (Flash)1× H100
Fine-tuning✓ Allowed
Hugging Face ↗

💡 No monthly fees. Cache hits save 90% on repeated system prompts. New accounts receive $5 in free API credits.

FAQ

Frequently Asked Questions

Is DeepSeek Coder really better than GPT-5 at coding?+

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.

What is DeepSeek Coder V2 and how does it differ from V4?+

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.

How do I use DeepSeek Coder for code completion in VS Code?+

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.

How many programming languages does DeepSeek Coder support?+

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.

Can I fine-tune DeepSeek Coder on my own codebase?+

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.

What's the difference between V4-Flash and V4-Pro for coding?+

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.

Does DeepSeek support function calling and structured output?+

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.

Get Started

Ready to code with frontier AI?

Join millions of developers building with the world's best open-source coding model. Start free — no credit card, no subscription, no limits.

Start Coding Free → Get API Key GitHub ↗