The Coding Leaderboard evaluates LLMs on their software engineering capabilities. From generating production-ready code across major programming languages to designing algorithms, debugging complex functions, and translating scientific concepts into executable scripts, this category measures a model’s ability to handle a broad range of coding and software development tasks.
Scores in this category are compiled from leading coding benchmarks highlighting models that perform well on code generation, debugging, problem-solving, and technical accuracy.
Need more than code generation? Coding performance accounts for 30% of our composite rating. Explore the Overall LLM Ranking to see which top coding models also excel at autonomous agent workflows, advanced mathematics, and complex reasoning.
| Rank | Model Name | Relative Quality | Score |
|---|---|---|---|
| 1 | Claude Opus 5.5 |
|
99.73 |
| 2 | Claude Sonnet 5.5 |
|
95.51 |
| 3 | GPT-6 Astra |
|
92.68 |
| 4 | GPT-5.6 Sol |
|
90.88 |
| 5 | Gemini 4 Argon |
|
89.42 |
| 6 | ERNIE 5.0 |
|
89.40 |
| 7 | Claude Fable 5.1 |
|
89.36 |
| 8 | GPT-6.1 Sol |
|
88.91 |
| 9 | Claude Fable 5 |
|
88.43 |
| 10 | Kimi K3 |
|
86.57 |
| 11 | Muse Spark 1.3 |
|
86.51 |
| 12 | Claude Opus 5 |
|
86.45 |
| 13 | ChatGPT-4o |
|
86.01 |
| 14 | GPT-5.6 Terra |
|
85.68 |
| 15 | Qwen3 VL 235B A22B |
|
85.42 |
| 16 | GPT-5.5 |
|
85.28 |
| 17 | GPT-5.5 Instant |
|
84.73 |
| 18 | GPT-6 Sol |
|
84.51 |
| 19 | MiMo-V2.6-Pro |
|
84.39 |
| 20 | GLM-5.3 |
|
84.28 |
| 21 | Mistral |
|
84.09 |
| 22 | GPT-5.6 Luna |
|
83.66 |
| 23 | DeepSeek-V4.1-Flash |
|
83.36 |
| 24 | Qwen3.8 |
|
82.35 |
| 25 | Grok 4.7 |
|
82.17 |
| 26 | Claude Opus 4.8 |
|
81.28 |
| 27 | Claude Opus 4.7 |
|
80.48 |
| 28 | Gemini 3.7 Flash |
|
80.41 |
| 29 | Ling 3.1 Flash |
|
80.23 |
| 30 | Grok 4.6 |
|
80.01 |
| 31 | DeepSeek-V4-Pro |
|
79.52 |
| 32 | Gemini 3.8 Flash |
|
79.47 |
| 33 | Claude Haiku 5.5 |
|
79.20 |
| 34 | GLM-5.3-Flash |
|
79.14 |
| 35 | GLM-5.2 |
|
79.06 |
| 36 | Step 5 |
|
78.64 |
| 37 | Muse Spark 1.1 |
|
78.59 |
| 38 | MiMo-V2.6-Flash |
|
78.53 |
| 39 | INTELLECT-3 |
|
78.50 |
| 40 | GLM-4.6V |
|
78.50 |
| 41 | Claude Sonnet 5 |
|
78.46 |
| 42 | Mistral Small |
|
77.91 |
| 43 | Hy4 |
|
77.64 |
| 44 | Ling-flash-2.0 |
|
77.61 |
| 45 | Mistral Large 4 |
|
77.47 |
| 46 | GPT-6 Luna |
|
77.46 |
| 47 | Claude Opus 4.6 |
|
77.44 |
| 48 | GLM-4.5V |
|
76.44 |
| 49 | Qwen2.5 |
|
76.44 |
| 50 | DeepSeek-V4-Flash |
|
76.39 |
| 51 | Qwen3.8-Flash-Next |
|
76.12 |
| 52 | Muse Spark 1.2 |
|
75.86 |
| 53 | Kimi K2.6 |
|
75.62 |
| 54 | Grok 4.5 |
|
75.52 |
| 55 | Qwen3.7 |
|
75.31 |
| 56 | Qwen3.8-27B |
|
75.20 |
| 57 | Gemini 3.5 Flash |
|
74.77 |
| 58 | Ring-flash-2.0 |
|
74.67 |
| 59 | Gemini 3.6 Flash |
|
74.45 |
| 60 | GPT-5 nano |
|
73.93 |
| 61 | Gemini 3.1 Pro |
|
73.82 |
| 62 | Claude Opus 4.5 |
|
73.47 |
| 63 | Olmo 3.1 32B |
|
73.34 |
| 64 | Qwen3.7-Plus |
|
73.32 |
| 65 | Grok Build 0.1 |
|
73.24 |
| 66 | Claude Sonnet 4.6 |
|
72.96 |
| 67 | Muse Spark |
|
71.17 |
| 68 | MiMo-V2.5-Pro |
|
70.76 |
| 69 | Hy3 |
|
70.71 |
| 70 | Qwen3.6 Plus |
|
70.67 |
| 71 | Olmo 3 32B Think |
|
70.25 |
| 72 | MiniMax M3 |
|
69.86 |
| 73 | GPT-5.4 |
|
69.82 |
| 74 | Seed 2.0 Pro |
|
69.49 |
| 75 | Mistral Large |
|
69.37 |
| 76 | Qwen3.6 |
|
69.11 |
| 77 | GLM-5.1 |
|
68.51 |
| 78 | DeepSeek V3.1 Terminus |
|
68.32 |
| 79 | Olmo 3.1 32B Think |
|
67.45 |
| 80 | Qwen3.6-27B |
|
67.12 |
| 81 | GPT-5 mini |
|
67.09 |
| 82 | GPT-5.2 |
|
67.02 |
| 83 | Kimi K2.7 Code |
|
67.02 |
| 84 | GPT-5.3 Codex |
|
67.02 |
| 85 | GPT-5.4 nano |
|
66.64 |
| 86 | Inkling |
|
66.44 |
| 87 | MiMo-V2-Omni |
|
66.33 |
| 88 | LongCat-Flash |
|
65.81 |
| 89 | Kimi K2 |
|
65.61 |
| 90 | Seed 2.1 Pro |
|
65.55 |
| 91 | Llama 3.1 Nemotron 70B |
|
65.54 |
| 92 | GPT-5.4 mini |
|
65.40 |
| 93 | Grok 4.3 |
|
65.07 |
| 94 | Step-3.5-Flash |
|
64.37 |
| 95 | Inkling-Small |
|
64.36 |
| 96 | MiMo-V2.5 |
|
64.31 |
| 97 | Claude Opus 4 |
|
64.21 |
| 98 | Granite 4.2 30B |
|
63.90 |
| 99 | MiniMax M2.7 |
|
63.47 |
| 100 | Gemini 3 Pro |
|
63.27 |