Evaluation Criteria

Not just one benchmark score. Comprehensive dimensions: SWE-bench (real GitHub issue fixes), HumanEval (function-level code gen), developer community feedback, multi-language coverage, and agent coding ability.

Rankings

Tier 1: Top Coding Models

  1. Claude Opus 4.7 (~72% SWE-bench) — Highest code quality, large project refactoring
  2. GPT-5.5 (~68%) — Best all-around, stable tool calling
  3. DeepSeek V4 Pro (~65%) — Best open-source, excellent value
  4. MiMo-V2.5 Pro (~63%) — Low price, million-token context

Tier 2: Excellent Coding Models

  1. Kimi K2.6 — Code reasoning, algorithms
  2. Qwen3.7 Max — Multi-language, enterprise dev
  3. Claude Sonnet 4.6 — Speed-quality balance
  4. GPT-5.5 Instant — Real-time completion

Tier 3: Adequate Models

9-14: DeepSeek Flash, MiMo-V2.5, Mistral, Llama, etc.

By Scenario

Large projects → Claude Opus 4.7 Daily dev → GPT-5.5 Instant or DeepSeek Flash Algorithms → Kimi K2.6 or DeepSeek V4 Pro Frontend → Gemini 3.5 Pro Local deployment → DeepSeek V4 Pro open-source Budget → DeepSeek Flash (¥0.95/M)

Key Observations

  1. Gaps are narrowing — Claude's lead over GPT/DeepSeek is shrinking
  2. Price ≠ ability — Claude costs 30x DeepSeek but is only ~10% better
  3. Open-source is "good enough" for 80% of coding tasks
  4. Agent coding is the new frontier — who can autonomously build a complete feature