qwen2.5-coder on RTX 3090 (24GB) + AMD EPYC 7663 56-Core Processor (56c) + 252GB
MeasuredOn 2026-07-02, qwen2.5-coder Q4_K_M ran at 39.9 tok/s (chat-short) on an RTX 3090 (24GB) with ollama. Run r_pb0jpnbujji.
RTX 3090 (24GB) + AMD EPYC 7663 56-Core Processor (56c) + 252GB
suite suite-v1
cli 0.0.3
signedi2Roip+TUP…
Embed badgesubmitted Jul 02, 2026Workload results
| Workload | Backend | Model | decode tok/s | prefill tok/s | TTFT | p50 | p95 |
|---|---|---|---|---|---|---|---|
| chat-short | ollama@0.31.1 | qwen2.5-coderQ4_K_M | 39.86tok/s | 2.83tok/s | 46,337ms | 7.1ms | 7.3ms |
| chat-long | ollama@0.31.1 | qwen2.5-coderQ4_K_M | 135.0tok/s | 3,319.4tok/s | 954ms | 7.4ms | 7.6ms |
| concurrent-decode | ollama@0.31.1 | qwen2.5-coderQ4_K_M | 139.2tok/s | — | — | 7.2ms | 7.3ms |
| agent-trace | ollama@0.31.1 | qwen2.5-coderQ4_K_M | 134.2tok/s | 4,111.1tok/s | 487ms | 7.5ms | 7.7ms |
Reproduce on your machine
Start with this model and workload selection. This command does not capture the original artifact, backend version or server settings:
Match quantization, context capacity, caching and runtime settings for a useful comparison. Duration varies by workload and hardware; the published client may differ from this run's version. How it's measured.
Share this run
Copy the short link, a Reddit-ready summary, or a README badge. Every number is the measured result on this page, and each badge links back to it.
https://llm-speed.com/r/r_pb0jpnbujjiRelated benchmarks
- More qwen2.5-coder benchmarks — every backend and rig that has run this model.
- More RTX 3090 (24GB) LLM benchmarks — every model measured on this hardware.
Provenance
- Run ID
- r_pb0jpnbujji
- Fingerprint hash
- Public key
- i2Roip+TUPwEFd03man/aR9MFyjxYHpCVeBLJRo7qAY=
- Received
- 2026-07-02 04:36:59