---
title: "Best AI Models for Coding (2026)"
type: comparison
id: "best-coding-models"
description: "Ranked list of the best AI models for software engineering. SWE-bench scores, coding benchmarks, pricing, and tool recommendations for each model."
last_updated: "2026-04-10"
tags:
- "coding"
- "swe-bench"
- "comparison"
- "software-engineering"
- "ranking"
---

# Best AI Models for Coding (2026)

Ranked by real-world software engineering capability. SWE-bench scores, benchmark numbers, pricing, and which coding tool to pair each model with.

## The Rankings

### #1: Claude Opus 4.6

| Metric | Score |
|--------|-------|
| Coding benchmark | 97/100 |
| SWE-bench | 80.8% |
| Reasoning | 96/100 |
| Context window | 1M tokens |
| Pricing | $5/$25 per 1M tokens |
| Speed | 62/100 |

The best coding model by a clear margin. 80.8% SWE-bench is the highest score any model has achieved. Opus 4.6 excels at complex multi-file refactors, understands large codebases holistically, and produces code that requires fewer corrections than any competitor. The 1M context window means it can hold an entire mid-size codebase in a single pass.

The tradeoffs are speed (62/100 -- it thinks carefully) and output cost ($25/M tokens -- the highest among frontier models). For complex coding work where accuracy matters, both are worth paying.

**Best coding tool:** Claude Code. The CLI agent is purpose-built for Claude and delivers the best agentic coding experience available.

### #2: MiniMax M2.7

| Metric | Score |
|--------|-------|
| Coding benchmark | 95/100 |
| SWE-bench | Not disclosed |
| Reasoning | 90/100 |
| Context window | 128K tokens |
| Pricing | $0.53/$0.53 per 1M tokens |
| Speed | 85/100 |

The open-source coding sleeper hit. 95/100 on coding benchmarks at $0.53 per million tokens for both input and output. That is roughly 1/50th of Opus's output cost with only a 2-point gap on coding scores. For autonomous coding agents that make many API calls, the economics are transformative.

The ecosystem is less mature (Chinese-first documentation, Modified MIT license) and the 128K context window is a quarter of Opus's. But for pure coding throughput on a budget, nothing comes close.

**Best coding tool:** Cursor (via custom API endpoint) or any tool supporting OpenAI-compatible APIs.

### #3: GLM-5

| Metric | Score |
|--------|-------|
| Coding benchmark | 93/100 |
| SWE-bench | 77.8% |
| Reasoning | 90/100 |
| Context window | 128K tokens |
| Pricing | Free (self-hosted) / Zhipu API |
| Speed | 70/100 |

The best open-source model for real-world software engineering by SWE-bench numbers. 77.8% puts it ahead of GPT-5.4 (74.9%) and every other open model. The MIT license with no usage restrictions makes it the cleanest option for enterprise self-hosting.

Requires serious hardware (8x A100 80GB for FP16), and the Western ecosystem is thin. But the numbers speak for themselves.

**Best coding tool:** Self-hosted with vLLM, accessible via Cursor or any OpenAI-compatible tool.

### #4: Claude Sonnet 4.6

| Metric | Score |
|--------|-------|
| Coding benchmark | 93/100 |
| SWE-bench | Not disclosed |
| Reasoning | 91/100 |
| Context window | 1M tokens |
| Pricing | $3/$15 per 1M tokens |
| Speed | 82/100 |

The daily-driver coding model. Sonnet 4.6 matches GLM-5's 93/100 coding score while being faster (82 vs 70 speed), cheaper than Opus, and backed by the full Anthropic ecosystem. It is the first Sonnet that beats a previous Opus generation in coding evaluations. The 1M context window at $3/$15 is excellent value.

For most developers, Sonnet 4.6 is the right default. You only need to step up to Opus for the hardest coding tasks.

**Best coding tool:** Claude Code (switches seamlessly between Sonnet and Opus) or Cursor.

### #5: GPT-5.4

| Metric | Score |
|--------|-------|
| Coding benchmark | 92/100 |
| SWE-bench | 74.9% |
| Reasoning | 95/100 |
| Context window | 1M tokens |
| Pricing | $5/$15 per 1M tokens |
| Speed | 80/100 |

Strong all-around, with the broadest ecosystem integration. 74.9% SWE-bench is solid -- below Claude's 80.8% but above most open models. GPT-5.4's real advantage for coding is ecosystem: GitHub Copilot is built on it, and the OpenAI Assistants API has the most mature third-party tooling.

The thinking variant (GPT-5.4 Thinking, 93/100 coding) is better for competition-level programming at $10/$40, but the base model handles most real-world coding well.

**Best coding tool:** GitHub Copilot (native integration) or Cursor.

### #6: Qwen 3.5 397B-A17B

| Metric | Score |
|--------|-------|
| Coding benchmark | 92/100 |
| SWE-bench | Not disclosed |
| Reasoning | 91/100 |
| Context window | 256K tokens |
| Pricing | Free (self-hosted) / Alibaba Cloud API |
| Speed | 82/100 |

The most well-rounded open-source option. Matches GPT-5.4 on coding (92/100) while being free to self-host under Apache 2.0. The 17B active parameters in a 397B MoE architecture means it runs on surprisingly reasonable hardware (single GPU with Q4 quantization). The 256K context window is better than most open models.

**Best coding tool:** Cursor (via custom API) or self-hosted with Ollama/vLLM.

### #7: Gemini 3.1 Pro

| Metric | Score |
|--------|-------|
| Coding benchmark | 91/100 |
| SWE-bench | Not disclosed |
| Reasoning | 93/100 |
| Context window | 1M tokens |
| Pricing | $2/$12 per 1M tokens |
| Speed | 78/100 |

Best value among proprietary models for coding. At $2/$12, it is 60% cheaper than Claude Opus on input and 52% cheaper on output, with a 91/100 coding score that handles most programming tasks well. The free tier through Google AI Studio makes it the easiest to start with.

**Best coding tool:** Google Antigravity (free, Gemini-native) or Cursor.

### #8: Nemotron-Cascade 2

| Metric | Score |
|--------|-------|
| Coding benchmark | 90/100 |
| SWE-bench | Not disclosed |
| Reasoning | 88/100 |
| Context window | 1M tokens |
| Pricing | Free (open weights) |
| Speed | 92/100 |

The best coding model you can run on consumer hardware. 90/100 coding with only 3B active parameters, running on a single RTX 4090. Gold medals at IOI and ICPC World Finals. 87.2% on LiveCodeBench v6. The hybrid Mamba-2 + Transformer architecture enables a 1M context window with sub-linear memory scaling.

If you want a local coding model that does not require enterprise GPU infrastructure, this is the answer.

**Best coding tool:** Ollama (for local serving) connected to Cursor or VS Code.

### #9: Qwen 3

| Metric | Score |
|--------|-------|
| Coding benchmark | 90/100 |
| SWE-bench | Not disclosed |
| Reasoning | 88/100 |
| Context window | 128K tokens |
| Pricing | Free (self-hosted) / Alibaba Cloud API |
| Speed | 80/100 |

Overtook Llama as the most-downloaded model family on HuggingFace. The Qwen3-Coder-Next variant is specifically optimized for code generation. Apache 2.0 license, massive community, and variants from 0.6B (phones) to 235B (multi-GPU). Best multilingual coding model (95/100 multilingual).

**Best coding tool:** Cursor or self-hosted with vLLM.

### #10: DeepSeek V3.2

| Metric | Score |
|--------|-------|
| Coding benchmark | 88/100 |
| SWE-bench | Not disclosed |
| Reasoning | 88/100 |
| Context window | 128K tokens |
| Pricing | $0.27/$1.10 per 1M tokens |
| Speed | 82/100 |

The cheapest capable coding model via API. At $0.27/$1.10, it costs roughly 5% of what GPT-5.4 charges with an 88/100 coding score. MIT license for self-hosting. For high-volume coding tasks where cost matters more than squeezing out the last few points of accuracy, V3.2 is the rational choice.

**Best coding tool:** Cursor (via OpenAI-compatible API).

## Coding Tool Recommendations

| Tool | Best For | Price |
|------|----------|-------|
| Claude Code | Professional software engineering, agentic coding, complex refactors | Included in Claude Pro ($20/mo) / Max ($100-200/mo) |
| GitHub Copilot | Broad IDE integration, code completion, GPT ecosystem users | $10-39/mo |
| Cursor | Model flexibility, trying different models, power users | $20/mo (Pro) |
| Google Antigravity | Free coding with Gemini and Claude, Google ecosystem users | Free |
| Amazon Kiro | Spec-driven development, AWS ecosystem, Bedrock model access | Preview pricing TBD |
| Windsurf | Integrated coding agent (now owned by Cognition/Devin) | $15/mo |

## The Verdict

**For professional software engineering:** Claude Opus 4.6 via Claude Code. The SWE-bench leadership translates directly to fewer bugs, better refactors, and less time spent correcting model output.

**For daily coding (best value):** Claude Sonnet 4.6 via Claude Code or Cursor. 93/100 coding at $3/$15 is 80% of Opus quality at 60% of the output cost.

**For budget-conscious coding:** MiniMax M2.7 ($0.53/M tokens) or DeepSeek V3.2 ($0.27/$1.10) via Cursor. Near-frontier coding at a fraction of the cost.

**For local/self-hosted coding:** Nemotron-Cascade 2 on consumer hardware (RTX 4090), or GLM-5 on enterprise hardware (8x A100). Both under permissive licenses.

**For coding in non-English languages:** Qwen 3 or Qwen 3.5. Best multilingual support with strong coding performance.

Best AI Models for Coding (2026)

Ranked by real-world software engineering capability. SWE-bench scores, benchmark numbers, pricing, and which coding tool to pair each model with.

The Rankings

#1: Claude Opus 4.6

Metric	Score
Coding benchmark	97/100
SWE-bench	80.8%
Reasoning	96/100
Context window	1M tokens
Pricing	$5/$25 per 1M tokens
Speed	62/100

The best coding model by a clear margin. 80.8% SWE-bench is the highest score any model has achieved. Opus 4.6 excels at complex multi-file refactors, understands large codebases holistically, and produces code that requires fewer corrections than any competitor. The 1M context window means it can hold an entire mid-size codebase in a single pass.

The tradeoffs are speed (62/100 -- it thinks carefully) and output cost ($25/M tokens -- the highest among frontier models). For complex coding work where accuracy matters, both are worth paying.

Best coding tool: Claude Code. The CLI agent is purpose-built for Claude and delivers the best agentic coding experience available.

#2: MiniMax M2.7

Metric	Score
Coding benchmark	95/100
SWE-bench	Not disclosed
Reasoning	90/100
Context window	128K tokens
Pricing	$0.53/$0.53 per 1M tokens
Speed	85/100

The open-source coding sleeper hit. 95/100 on coding benchmarks at $0.53 per million tokens for both input and output. That is roughly 1/50th of Opus's output cost with only a 2-point gap on coding scores. For autonomous coding agents that make many API calls, the economics are transformative.

The ecosystem is less mature (Chinese-first documentation, Modified MIT license) and the 128K context window is a quarter of Opus's. But for pure coding throughput on a budget, nothing comes close.

Best coding tool: Cursor (via custom API endpoint) or any tool supporting OpenAI-compatible APIs.

#3: GLM-5

Metric	Score
Coding benchmark	93/100
SWE-bench	77.8%
Reasoning	90/100
Context window	128K tokens
Pricing	Free (self-hosted) / Zhipu API
Speed	70/100

The best open-source model for real-world software engineering by SWE-bench numbers. 77.8% puts it ahead of GPT-5.4 (74.9%) and every other open model. The MIT license with no usage restrictions makes it the cleanest option for enterprise self-hosting.

Requires serious hardware (8x A100 80GB for FP16), and the Western ecosystem is thin. But the numbers speak for themselves.

Best coding tool: Self-hosted with vLLM, accessible via Cursor or any OpenAI-compatible tool.

#4: Claude Sonnet 4.6

Metric	Score
Coding benchmark	93/100
SWE-bench	Not disclosed
Reasoning	91/100
Context window	1M tokens
Pricing	$3/$15 per 1M tokens
Speed	82/100

The daily-driver coding model. Sonnet 4.6 matches GLM-5's 93/100 coding score while being faster (82 vs 70 speed), cheaper than Opus, and backed by the full Anthropic ecosystem. It is the first Sonnet that beats a previous Opus generation in coding evaluations. The 1M context window at $3/$15 is excellent value.

For most developers, Sonnet 4.6 is the right default. You only need to step up to Opus for the hardest coding tasks.

Best coding tool: Claude Code (switches seamlessly between Sonnet and Opus) or Cursor.

#5: GPT-5.4

Metric	Score
Coding benchmark	92/100
SWE-bench	74.9%
Reasoning	95/100
Context window	1M tokens
Pricing	$5/$15 per 1M tokens
Speed	80/100

Strong all-around, with the broadest ecosystem integration. 74.9% SWE-bench is solid -- below Claude's 80.8% but above most open models. GPT-5.4's real advantage for coding is ecosystem: GitHub Copilot is built on it, and the OpenAI Assistants API has the most mature third-party tooling.

The thinking variant (GPT-5.4 Thinking, 93/100 coding) is better for competition-level programming at $10/$40, but the base model handles most real-world coding well.

Best coding tool: GitHub Copilot (native integration) or Cursor.

#6: Qwen 3.5 397B-A17B

Metric	Score
Coding benchmark	92/100
SWE-bench	Not disclosed
Reasoning	91/100
Context window	256K tokens
Pricing	Free (self-hosted) / Alibaba Cloud API
Speed	82/100

The most well-rounded open-source option. Matches GPT-5.4 on coding (92/100) while being free to self-host under Apache 2.0. The 17B active parameters in a 397B MoE architecture means it runs on surprisingly reasonable hardware (single GPU with Q4 quantization). The 256K context window is better than most open models.

Best coding tool: Cursor (via custom API) or self-hosted with Ollama/vLLM.

#7: Gemini 3.1 Pro

Metric	Score
Coding benchmark	91/100
SWE-bench	Not disclosed
Reasoning	93/100
Context window	1M tokens
Pricing	$2/$12 per 1M tokens
Speed	78/100

Best value among proprietary models for coding. At $2/$12, it is 60% cheaper than Claude Opus on input and 52% cheaper on output, with a 91/100 coding score that handles most programming tasks well. The free tier through Google AI Studio makes it the easiest to start with.

Best coding tool: Google Antigravity (free, Gemini-native) or Cursor.

#8: Nemotron-Cascade 2

Metric	Score
Coding benchmark	90/100
SWE-bench	Not disclosed
Reasoning	88/100
Context window	1M tokens
Pricing	Free (open weights)
Speed	92/100

The best coding model you can run on consumer hardware. 90/100 coding with only 3B active parameters, running on a single RTX 4090. Gold medals at IOI and ICPC World Finals. 87.2% on LiveCodeBench v6. The hybrid Mamba-2 + Transformer architecture enables a 1M context window with sub-linear memory scaling.

If you want a local coding model that does not require enterprise GPU infrastructure, this is the answer.

Best coding tool: Ollama (for local serving) connected to Cursor or VS Code.

#9: Qwen 3

Metric	Score
Coding benchmark	90/100
SWE-bench	Not disclosed
Reasoning	88/100
Context window	128K tokens
Pricing	Free (self-hosted) / Alibaba Cloud API
Speed	80/100

Overtook Llama as the most-downloaded model family on HuggingFace. The Qwen3-Coder-Next variant is specifically optimized for code generation. Apache 2.0 license, massive community, and variants from 0.6B (phones) to 235B (multi-GPU). Best multilingual coding model (95/100 multilingual).

Best coding tool: Cursor or self-hosted with vLLM.

#10: DeepSeek V3.2

Metric	Score
Coding benchmark	88/100
SWE-bench	Not disclosed
Reasoning	88/100
Context window	128K tokens
Pricing	$0.27/$1.10 per 1M tokens
Speed	82/100

The cheapest capable coding model via API. At $0.27/$1.10, it costs roughly 5% of what GPT-5.4 charges with an 88/100 coding score. MIT license for self-hosting. For high-volume coding tasks where cost matters more than squeezing out the last few points of accuracy, V3.2 is the rational choice.

Best coding tool: Cursor (via OpenAI-compatible API).

Coding Tool Recommendations

Tool	Best For	Price
Claude Code	Professional software engineering, agentic coding, complex refactors	Included in Claude Pro ($20/mo) / Max ($100-200/mo)
GitHub Copilot	Broad IDE integration, code completion, GPT ecosystem users	$10-39/mo
Cursor	Model flexibility, trying different models, power users	$20/mo (Pro)
Google Antigravity	Free coding with Gemini and Claude, Google ecosystem users	Free
Amazon Kiro	Spec-driven development, AWS ecosystem, Bedrock model access	Preview pricing TBD
Windsurf	Integrated coding agent (now owned by Cognition/Devin)	$15/mo

The Verdict

For professional software engineering: Claude Opus 4.6 via Claude Code. The SWE-bench leadership translates directly to fewer bugs, better refactors, and less time spent correcting model output.

For daily coding (best value): Claude Sonnet 4.6 via Claude Code or Cursor. 93/100 coding at $3/$15 is 80% of Opus quality at 60% of the output cost.

For budget-conscious coding: MiniMax M2.7 ($0.53/M tokens) or DeepSeek V3.2 ($0.27/$1.10) via Cursor. Near-frontier coding at a fraction of the cost.

For local/self-hosted coding: Nemotron-Cascade 2 on consumer hardware (RTX 4090), or GLM-5 on enterprise hardware (8x A100). Both under permissive licenses.

For coding in non-English languages: Qwen 3 or Qwen 3.5. Best multilingual support with strong coding performance.