Qwen3.8-27B on RTX 5090 (32GB) + AMD EPYC 9534 64-Core Processor (128c) + 756GB
MeasuredOn 2026-10-15, Qwen3.8-27B Q4_K_M ran at 75.2 tok/s (chat-short) on an RTX 5090 (32GB) with llama.cpp. Run r_qfrb2zmyk0k.
RTX 5090 (32GB) + AMD EPYC 9534 64-Core Processor (128c) + 756GB
suite suite-v1
cli 0.0.7
signed+I19MG+nHS…
Embed badgesubmitted Oct 15, 2026Workload results
| Workload | Backend | Model | decode tok/s | prefill tok/s | TTFT | p50 | p95 |
|---|---|---|---|---|---|---|---|
| chat-short | llama.cpp@0.7.0-dev (build 11669, commit 620d2225c) | Qwen3.8-27BQ4_K_M | 75.19tok/s | 563.4tok/s | 273ms | 13.2ms | 13.4ms |
| chat-long | llama.cpp@0.7.0-dev (build 11669, commit 620d2225c) | Qwen3.8-27BQ4_K_M | 74.57tok/s | 2,499.5tok/s | 1,290ms | 13.3ms | 13.5ms |
| concurrent-decode | llama.cpp@0.7.0-dev (build 11669, commit 620d2225c) | Qwen3.8-27BQ4_K_M | 75.40tok/s | — | — | 13.2ms | 13.4ms |
| agent-trace | llama.cpp@0.7.0-dev (build 11669, commit 620d2225c) | Qwen3.8-27BQ4_K_M | 73.52tok/s | 5,065.3tok/s | 436ms | 13.3ms | 13.6ms |
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_qfrb2zmyk0kRelated benchmarks
- More Qwen3.8-27B benchmarks — every backend and rig that has run this model.
- More RTX 5090 (32GB) LLM benchmarks — every model measured on this hardware.
Provenance
- Run ID
- r_qfrb2zmyk0k
- Fingerprint hash
- Public key
- +I19MG+nHSsGvJZ/HcJHaLYQg+adpxZbbIDZsTLyNPE=
- Received
- 2026-10-15 17:11:30