RankLLMs: AI Model Leaderboard & LLM Benchmarks
RankLLMs is the independent AI model leaderboard. Compare LLMs on real-world coding benchmarks, reasoning accuracy, tokens per second, and API inference pricing.
AI Model Leaderboard
Empirically evaluated on reasoning (GPQA/MATH), SWE-bench coding, agentic autonomy, inference throughput (tps), and API pricing.
| Rank | Model & Provider | Overall Score | Reasoning | Coding | Speed | Cost / 1M | Actions |
|---|---|---|---|---|---|---|---|
| #1 | GPT-6 AstraNEW OpenAI•Proprietary | 68.5 | 96.0 | 74.1 | 59 tps | $10.00 | |
| #2 | Anthropic•Proprietary | 66.8 | 88.5 | 86.2 | 42 tps | $5.00 | |
| #3 | Anthropic•Proprietary | 64.2 | 93.7 | 67.4 | 65 tps | $10.00 | |
| #4 | Anthropic•Proprietary | 62.0 | 67.5 | 84.5 | 110 tps | $10.00 | |
| #5 | GPT-6 SolNEW OpenAI•Proprietary | 60.5 | 78.5 | 84.8 | 126 tps | $2.00 | |
| #6 | Claude Mythos PreviewUNRELEASED Anthropic•Proprietary | 58.2 | 65.8 | 82.2 | 50 tps | $0.00 | |
| #7 | Anthropic•Proprietary | 57.5 | 64.5 | 81.8 | 68 tps | $5.00 | |
| #8 | Meta•Proprietary | 57.4 | 63.5 | 75.4 | 221 tps | $1.25 | |
| #9 | OpenAI•Proprietary | 57.2 | 65.5 | 81.2 | 89 tps | $4.00 | |
| #10 | Google•Proprietary | 56.8 | 62.5 | 73.7 | 297 tps | $0.75 | |
| #11 | Xiaomi•Proprietary | 56.5 | 65.2 | 78.4 | 55 tps | $0.44 | |
| #12 | Moonshot AI•Open Source | 56.0 | 64.2 | 80.5 | 52 tps | Free/Open Source | |
| #13 | Qwen / Alibaba•Proprietary | 55.8 | 62.8 | 79.4 | 39 tps | $2.00 | |
| #14 | Zhipu AI•Open Source | 55.8 | 60.5 | 78.2 | 61 tps | Free/Open Source | |
| #15 | xAI•Proprietary | 55.6 | 63.2 | 78.5 | 59 tps | $2.00 | |
| #16 | GLM-5.3NEW Zhipu AI•Open Source | 55.4 | 62.5 | 77.8 | 57 tps | $1.40 | |
| #17 | Hy4 PreviewNEW Tencent•Open Source | 55.2 | 58.5 | 77.0 | 60 tps | Free/Open Source | |
| #18 | OpenAI•Proprietary | 55.0 | 59.2 | 77.4 | 117 tps | $2.00 | |
| #19 | Anthropic•Proprietary | 54.8 | 59.5 | 76.5 | 57 tps | $5.00 | |
| #20 | Anthropic•Proprietary | 54.8 | 58.6 | 75.8 | 77 tps | $2.00 | |
| #21 | DeepSeek•Open Source | 54.4 | 62.5 | 81.0 | 176 tps | Free/Open Source | |
| #22 | DeepSeek•Open Source | 54.2 | 58.4 | 80.6 | 50 tps | $1.74 | |
| #23 | Google•Proprietary | 54.2 | 61.5 | 78.6 | 169 tps | $0.75 | |
| #24 | Anthropic•Proprietary | 54.0 | 57.2 | 72.4 | 35 tps | $5.00 | |
| #25 | OpenAI•Proprietary | 53.8 | 58.2 | 72.5 | 14 tps | $2.50 |
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Frequently Asked Questions About LLM Benchmarks
Clear answers to common technical questions about Large Language Model evaluation and API selection.
What is RankLLMs?
RankLLMs is an independent AI benchmark leaderboard and Large Language Model comparison platform. We provide objective, reproducible evaluations of proprietary and open-weights models based on coding accuracy, mathematical reasoning, tokens-per-second speed, and real-world API inference costs.
What is the highest-ranked AI model in 2026?
OpenAI's GPT-6 Astra currently holds the #1 overall position on RankLLMs with a composite score of 68.5, followed by Anthropic's Claude Fable 5.1 (64.2) and Claude Fable 5 (62.0). For open-source and open-weights models, Moonshot AI's Kimi K3 (56.0), Alibaba's Qwen3.8 Max (55.8), and Zhipu AI's GLM-5.3-Flash (55.8) lead the global rankings.
How are LLM benchmark scores measured on RankLLMs?
RankLLMs aggregates standardized evaluation frameworks including multi-file repository coding benchmarks, mathematical reasoning, Code Arena Elo rankings, and agentic tool-use capability, combined with verified inference speed (tokens/sec and Time-To-First-Token) and API token pricing per 1M tokens.
Which LLM is best for autonomous coding and software engineering?
OpenAI's GPT-6 Astra (88.5 Coding) and Anthropic's Claude Fable 5.1 (86.0 Coding) and Claude Fable 5 (84.5 Coding) rank highest among proprietary systems. For open-weights software development, Moonshot AI's Kimi K3 (80.5 Coding), Alibaba's Qwen3.8 Max (79.4 Coding), and Zhipu AI's GLM-5.3-Flash (78.2 Coding) provide near-commercial performance at a fraction of API token costs.
What are the fastest and most affordable open-weights models?
DeepSeek-V4-Flash-0731 ($0.14/M tokens at 176 tokens/sec), GLM-5.3-Flash ($0.19/M tokens), and Poolside Laguna S 2.1 ($0.11/M tokens) offer state-of-the-art inference efficiency for high-throughput enterprise pipelines.
How often is the RankLLMs leaderboard updated?
The RankLLMs leaderboard is continuously updated whenever foundation model providers (OpenAI, Anthropic, Google, DeepSeek, Zhipu AI, Moonshot AI, Alibaba Cloud / Qwen Team, Meta, xAI, ByteDance, MiniMax) release new model checkpoints, benchmark evaluations, or update their public API token pricing.
Independent Empirical AI Benchmarks
RankLLMs delivers reproducible, empirical evaluations across proprietary and open-weights Large Language Models. Every score is derived from verified test harness runs across standardized benchmarks—including SWE-bench Verified coding problem resolution, GPQA Diamond mathematical reasoning, and live API streaming throughput tests. We do not accept sponsored rankings or vendor-submitted synthetic scores.
Inference pricing is audited daily against published provider rate cards in USD ($/1M blended tokens), and model checkpoints are continuously updated to reflect real-world developer adoption. Read our complete testing criteria in our Evaluation Methodology or review our Editorial Standards.