The definitive ranking of AI models for software development, code generation, and programming tasks based on LiveCodeBench, Terminal-Bench, and SciCode benchmarks. Rankings are based on LiveCodeBench, Terminal-Bench, and SciCode benchmarks from independent evaluations.
Quality Index
61
ByteDance Seed
Quality Index
50.5
OpenAI
Quality Index
49.1
Anthropic
| Rank | Model | Quality | LiveCodeBench | Terminal-Bench | SciCode | License |
|---|---|---|---|---|---|---|
| 1 | Doubao-Seed-1.8 ByteDance Seed | 61 | 75% | 21% | 45% | Proprietary |
| 2 | GPT-5.2 (xhigh) OpenAI | 50.5 | 89% | 44% | 52% | Proprietary |
| 3 | Claude Opus 4.5 (high) Anthropic | 49.1 | 87% | 44% | 50% | Proprietary |
| 4 | Gemini 3 Pro Preview (high) | 47.9 | 92% | 39% | 56% | Proprietary |
| 5 | GPT-5.1 (high) OpenAI | 47 | 87% | 43% | 43% | Proprietary |
| 6 | Gemini 3 Flash | 45.9 | 91% | 36% | 51% | Proprietary |
| 7 | Claude 4.5 Sonnet Anthropic | 42.4 | 71% | 33% | 45% | Proprietary |
| 8 | GLM-4.7 (Thinking) Z AI | 41.7 | 89% | 30% | 45% | Open |
Our coding model rankings are based on three key benchmarks that evaluate real-world programming capabilities:
Evaluates code generation across multiple programming languages with fresh, contamination-free problems.
Tests complex terminal operations, DevOps tasks, and system-level programming capabilities.
Measures scientific computing and research-oriented programming across multiple domains.
Use our interactive comparison tool to explore pricing, latency, and benchmark scores for all 8 coding models.
As of January 2026, Doubao-Seed-1.8 leads our coding benchmarks with a75% score on LiveCodeBench. For open source alternatives, GLM-4.7 Thinking and DeepSeek V3.2 offer comparable performance at a fraction of the cost.
For professional software development, we recommend Claude Opus 4.5 for its excellent code review and debugging capabilities, or GPT-5.2 (xhigh) for complex architectural decisions. Both score above 85% on LiveCodeBench and excel at multi-file code understanding.
Yes, open source models have closed the gap significantly. GLM-4.7 Thinking achieves 89% on LiveCodeBench compared to GPT-5.2's 89%, while being free to self-host. The main tradeoff is in latency and ease of deployment, not raw capability.