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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 | Ministral-3-14B-Reasoning-251214BQ4_K_MMistral AI Performance benchmarkTimebench 3 - Kombi (Prefill + Generation) | 60,39 tok/s TG Prefill 1.497 · TTFT 8.155 ms | 5× | 2x NVIDIA GeForce RTX 2060Intel(R) Core(TM) i5-7400 CPU @ 3.00GHz · 7 GB RAM | llama.cppopenclaw_cli | Details → | |
| 2 | Ministral-3-14B-Reasoning-251214BQ4_K_MMistral AI Performance benchmarkTimebench 3 - Kombi (Prefill + Generation) | 29,08 tok/s TG Prefill 1.083 · TTFT 2.088 ms | 1× | 2x NVIDIA GeForce RTX 2060Intel(R) Core(TM) i5-7400 CPU @ 3.00GHz · 7 GB RAM | llama.cppopenclaw_cli | Details → |