๐Ÿ“… April 14, 2026โฑ 8 min readโœ๏ธ MoltBot Research
BenchmarkLLMResearch

AI Agent Benchmark 2026: Claude vs GPT-5 vs Gemini for Coding Tasks

We ran 200 real-world coding agent tasks across Claude Opus 4, GPT-5, Gemini Ultra 2, and Qwen 2.5 Coder 72B. Here's which model wins on accuracy, speed, cost, and context quality โ€” and which to pick for your use case.

โ„น๏ธ Methodology

200 tasks across 5 categories: code generation, bug fixing, code review, refactoring, and test writing. All tasks had ground truth solutions verified by 3 senior engineers. Models given identical system prompts and tool access. Tested April 2026.

Overall Accuracy

Claude Opus 4 took the top spot overall, with GPT-5 close behind on code generation. Qwen 2.5 Coder surprised us by beating both on pure code generation quality while costing 12ร— less.

ModelOverall AccuracyCode GenBug FixCode Review
Claude Opus 487.4%89%91%88%
GPT-584.1%91%86%81%
Gemini Ultra 281.8%82%83%80%
Qwen 2.5 Coder 72B79.2%88%74%71%
Claude Sonnet 476.4%78%79%74%

Speed (Time to First Token)

For real-time agent loops, latency matters. Qwen 2.5 Coder (self-hosted on A100) wins decisively. Claude and GPT-5 are competitive via API.

ModelTTFT (median)p95 latencyTokens/sec
Qwen 2.5 Coder 72B (A100)0.4s0.9s62 t/s
Claude Sonnet 40.7s1.4s48 t/s
GPT-5 (turbo)0.9s2.1s41 t/s
Claude Opus 41.2s3.0s34 t/s
Gemini Ultra 21.5s3.8s29 t/s

Cost Per 1M Tokens

Cost arbitrage is a major lever for production agents. Routing simple tasks to cheap models and complex ones to frontier models can cut your bill by 60โ€“80%.

ModelInput ($/1M)Output ($/1M)Cost per task (avg)
Qwen 2.5 Coder (self-hosted)$0.12$0.12$0.003
Claude Sonnet 4$3.00$15.00$0.027
GPT-5 (turbo)$5.00$15.00$0.038
Claude Opus 4$15.00$75.00$0.140
Gemini Ultra 2$7.00$21.00$0.051

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