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Rankings
LLM Leaderboard
Real measurements of every tested language model on real, named hardware – rated by raw speed (performance in tokens per second, prefill and time to first token) and by practical task quality in complete agent and chat runs (harness). Pick a benchmark type below or filter by model, maker and hardware to see exactly what is tested and how the results are produced.
⚡ Performance (tok/s)🤖 Harness quality👥 Concurrency🖥️ real hardware
| # | Model / Maker | Metrics | Parallel | GPU / CPU / RAM | Runtime | ||
|---|---|---|---|---|---|---|---|
| 1 | Ling-3.0-flash127.5BinclusionAI Performance benchmarkTimebench 3 - Kombi (Prefill + Generation) | 388,05 tok/s TG Prefill 16.198 · TTFT 2.053 ms | 10× | 2x NVIDIA RTX A6000AMD EPYC 7203P 8-Core Processor · 252 GB RAM | vLLMgodclawINT4 | Details → | |
| 2 | Ling-3.0-flash127.5BinclusionAI Performance benchmarkTimebench 3 - Kombi (Prefill + Generation) | 343,90 tok/s TG Prefill 9.629 · TTFT 1.973 ms | 5× | 2x NVIDIA RTX A6000AMD EPYC 7203P 8-Core Processor · 252 GB RAM | vLLMgodclawINT4 | Details → | |
| 3 | Ling-3.0-flash127.5BinclusionAI Performance benchmarkTimebench 3 - Kombi (Prefill + Generation) | 99,60 tok/s TG Prefill 4.438 · TTFT 606 ms | 1× | 2x NVIDIA RTX A6000AMD EPYC 7203P 8-Core Processor · 252 GB RAM | vLLMgodclawINT4 | Details → |