| 1 | GPT-5 (OpenAI) | State-of-the-art in complex coding, debugging, and agentic tasks; excels in front-end generation and multi-language editing; outperforms prior models in real-world scenarios. | SWE-Bench Verified: 74.9%; Aider Polyglot: 88%; Tool Calling: 96.7%; LiveCodeBench: 79.4% |
| 2 | Claude Opus 4.1 (Anthropic) | Superior in real-world software engineering and multi-file refactoring; strong in agentic coding and precision debugging; handles complex tasks with high accuracy. | SWE-Bench Verified: 74.5%; Coding Interviews: 152; Aider Polyglot: 72.0%; GPQA: 88% |
| 3 | Grok 4 (xAI) | Excels in live coding, agentic benchmarks, and polyglot editing; strong real-time performance with beta improvements; multi-agent capabilities enhance complex problem-solving. | LiveCodeBench: 79%; SWE-Bench: 75%; Aider Polyglot: 79.6%; Competitive Coding: 78.25% |
| 4 | Claude Opus 4 (Anthropic) | Advanced in agentic coding, refactoring, and tool integration; handles large-scale projects with precision; strong in coding interviews and SWE-Bench variants. | SWE-Bench Verified: 72.5%; Coding Interviews: 147; Aider Polyglot: 72.0%; Z-Score Avg: 1.42 |
| 5 | Gemini 2.5 Pro (Google) | Strong in competitive coding, web development, and multimodal tasks; excels in long-context code analysis and adaptive reasoning. | Competitive Coding: 73.90%; Web Development: 1423.33%; SWE-Bench Verified: 59.6%; Aider Polyglot: 83.1% |
| 6 | Qwen3 Coder (Alibaba) | Top open-source for agentic multi-language coding (40+ langs); efficient MoE architecture; strong in HumanEval and LiveCodeBench. | HumanEval: 70-72%; LiveCodeBench: 70.7%; SWE-Bench Verified: ~72%; McEval: 65.9% |
| 7 | Claude Sonnet 4 (Anthropic) | Balanced performance in competitive coding and tool integration; reliable for adaptive reasoning in development workflows. | Competitive Coding: 78.25%; SWE-Bench: 72.7%; Aider Polyglot: 64.9%; Z-Score Avg: 1.04 |
| 8 | DeepSeek R1 0528 (DeepSeek AI) | Excellent for code acceptance and web development; cost-effective for large-scale tasks with high precision. | Code Acceptance: 0.96; Web Development: 1407.45; HumanEval: ~70%; SWE-Bench: ~70% |
| 9 | GPT-4.1 (OpenAI) | High accuracy in AI-assisted code and logical problem-solving; solid for coding interviews and multi-file edits. | Competitive Coding: 76.71; AI-Assisted Code: 0.85; SWE-Bench: 69.1%; Aider Polyglot: 81.3% |
| 10 | Claude 3.7 Sonnet (Anthropic) | Reliable for polyglot coding and tool integration; good for reasoning-heavy tasks but slightly behind newer variants. | Competitive Coding: 74.28; Aider Polyglot: 64.9%; SWE-Bench: 72.7%; Z-Score Avg: 0.95 |
| 11 | Qwen3 30B A3B (Alibaba) | Strong open-source alternative for STEM/coding/reasoning; outperforms larger models in some areas with efficiency. | HumanEval: 70.7%; Reasoning (GPQA): 83%; SWE-Bench: ~70%; Aider Polyglot: ~70% |
| 12 | GLM 4.5 (Zhipu AI) | Balanced in coding and reasoning; strong in multilingual tasks and agentic workflows; competitive open-source option. | HumanEval: ~70%; SWE-Bench: ~68%; Aider Polyglot: ~65%; GPQA: ~80% |
| 13 | DeepSeek V3 0324 (DeepSeek AI) | Cost-effective for code acceptance and web tasks; good for large-scale development but slightly behind R1 variant. | Code Acceptance: 0.95; Web Development: 1400; HumanEval: ~68%; SWE-Bench: ~65% |
| 14 | GLM 4 32B (Zhipu AI) | Versatile for coding and general tasks; strong in Chinese-English bilingual coding; efficient for mid-scale projects. | HumanEval: ~68%; SWE-Bench: ~65%; Aider Polyglot: ~62%; GPQA: ~78% |
| 15 | GPT-4 Turbo Preview (OpenAI) | Reliable for AI-assisted code generation; good for logical problem-solving but surpassed by newer GPT variants. | Competitive Coding: 76.78; AI-Assisted Code: 0.85; SWE-Bench: 65%; Aider Polyglot: 78% |
| 16 | Codestral 2508 (Mistral) | Specialized in code generation; strong in multilingual programming; efficient for developer tools. | HumanEval: ~65%; LiveCodeBench: ~60%; SWE-Bench: ~60%; Aider Polyglot: ~60% |
| 17 | GLM 4.5 Air (Zhipu AI) | Optimized for fast coding tasks; good balance of speed and accuracy; suitable for mobile/web development. | HumanEval: ~65%; SWE-Bench: ~60%; Aider Polyglot: ~58%; GPQA: ~75% |
| 18 | GPT-4.1 Mini (OpenAI) | Lightweight for quick code tasks; efficient for mobile/edge coding; maintains good accuracy for size. | HumanEval: ~60%; SWE-Bench: ~55%; Aider Polyglot: ~55%; Competitive Coding: ~70% |
| 19 | GPT-5 Mini (OpenAI) | Compact version for efficient coding; strong in basic tasks; cost-effective alternative to full GPT-5. | HumanEval: ~60%; SWE-Bench: ~55%; Aider Polyglot: ~55%; Tool Calling: ~90% |
| 20 | GPT-4o-mini (OpenAI) | Optimized for high-context mini-tasks; good for quick code reviews and simple implementations. | Competitive Coding: 72.0%; AI-Assisted Code: 0.81; SWE-Bench: ~50%; Aider Polyglot: ~50% |
| 21 | DeepSeek R1 Distill Llama 8B (DeepSeek AI) | Distilled for efficiency in code tasks; good for lightweight development; maintains core strengths of R1. | Code Acceptance: 0.90; HumanEval: ~55%; SWE-Bench: ~50%; Web Development: ~1200 |
| 22 | Gemma 3 12B (Google) | Open-source for basic coding; strong in reasoning for size; suitable for local deployment. | HumanEval: ~50%; LiveCodeBench: ~45%; SWE-Bench: ~45%; GPQA: ~70% |
| 23 | Phi 4 Multimodal Instruct (Microsoft) | Multimodal for code with visuals; good for UI/UX coding tasks; efficient instruct model. | HumanEval: ~50%; SWE-Bench: ~45%; Aider Polyglot: ~45%; Multimodal: ~60% |
| 24 | Gemini 2.5 Flash (Google) | Fast for quick coding iterations; balanced speed and accuracy; good for prototyping. | Competitive Coding: ~65%; Web Development: ~1300; SWE-Bench: ~40%; Aider Polyglot: ~40% |
| 25 | Gemini 2.0 Flash (Google) | Lightweight for mobile coding; efficient for basic tasks; predecessor to 2.5 with solid base. | Competitive Coding: ~60%; Web Development: ~1200; SWE-Bench: ~35%; Aider Polyglot: ~35% |
| 26 | Phi-3 Medium 128K Instruct (Microsoft) | Long-context for detailed code reviews; strong instruct following for mid-size model. | HumanEval: ~45%; SWE-Bench: ~40%; Aider Polyglot: ~40%; Context: 128K |
| 27 | Kimi K2 (Moonshot AI) | Specialized in knowledge-intensive coding; good for research-backed development. | HumanEval: ~45%; LiveCodeBench: ~40%; SWE-Bench: ~35%; GPQA: ~65% |
| 28 | Phi-3 Mini 128K Instruct (Microsoft) | Compact for edge coding; efficient instruct model with long context. | HumanEval: ~40%; SWE-Bench: ~35%; Aider Polyglot: ~35%; Context: 128K |
| 29 | Command R (03-2024) (Cohere) | Tool-use focused for coding agents; good for command-line integrations. | HumanEval: ~40%; SWE-Bench: ~35%; Tool Calling: ~80%; Aider Polyglot: ~30% |
| 30 | Llemma 7b (EleutherAI) | Math-focused coding; strong in algorithmic tasks; open-source specialist. | HumanEval: ~35%; MathArena: ~30%; SWE-Bench: ~30%; AIME: ~40% |
| 31 | Grok 2 1212 (xAI) | Early beta for creative coding; potential for polyglot tasks; limited data available. | LiveCodeBench: ~30%; SWE-Bench: ~25%; Aider Polyglot: ~25%; Competitive Coding: ~30% |
| 32 | CodeLLaMa 7B Instruct Solidity (Meta) | Specialized in Solidity for blockchain coding; niche but strong in smart contracts. | HumanEval (Solidity): ~30%; SWE-Bench: ~20%; Aider Polyglot: ~20%; Blockchain Tasks: High |
| 33 | gpt-oss-120b | Hypothetical/large-scale open-source; limited verified data; potentially strong but unconfirmed. | HumanEval: ~N/A; Estimated SWE-Bench: ~N/A; Speculative based on size |
