🏆
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 | Nemotron-Cascade-2-30B-A3BNVIDIA PerformancebenchmarkTimebench 3 - Kombi (Prefill + Generation) | 5,86 tok/s TG Prefill 61 · TTFT 35.481 ms | 1× | Keine GPU (CPU-only)51x Intel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz · 504 GB RAM | llama.cppgodclawQ4_K_M | Details → | |
| 2 | Nemotron-Cascade-2-30B-A3BNVIDIA PerformancebenchmarkTimebench 3 - Kombi (Prefill + Generation) | 5,33 tok/s TG Prefill 74 · TTFT 150.609 ms | 5× | Keine GPU (CPU-only)51x Intel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz · 504 GB RAM | llama.cppgodclawQ4_K_M | Details → | |
| 3 | Nemotron-Cascade-2-30B-A3BNVIDIA PerformancebenchmarkTimebench 3 - Kombi (Prefill + Generation) | 0,27 tok/s TG Prefill 82 · TTFT 204.776 ms | 10× | Keine GPU (CPU-only)51x Intel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz · 504 GB RAM | llama.cppgodclawQ4_K_M | Details → |