Qwen3.8-27B-ctx4k on RTX 3090 (24GB)
MeasuredOn 2026-10-22, Qwen3.8-27B-ctx4k Q4_K_M ran at 38.6 tok/s (chat-short) on an RTX 3090 (24GB) with llama.cpp. Run r_mmtzel_i367.
Workload results
| Workload | Backend | Model | decode tok/s | prefill tok/s | TTFT | p50 | p95 |
|---|---|---|---|---|---|---|---|
| chat-short | llama.cpp@0.7.0-dev (build 11803, commit a37cc4610) | Qwen3.8-27B-ctx4kQ4_K_M | 38.61tok/s | 482.3tok/s | 319ms | 25.8ms | 26.3ms |
| chat-long | llama.cpp@0.7.0-dev (build 11803, commit a37cc4610) | Qwen3.8-27B-ctx4kQ4_K_M | 38.19tok/s | 1,222.7tok/s | 2,637ms | 26.1ms | 26.6ms |
| concurrent-decode | llama.cpp@0.7.0-dev (build 11803, commit a37cc4610) | Qwen3.8-27B-ctx4kQ4_K_M | 38.53tok/s | — | — | 25.9ms | 26.0ms |
| agent-trace | llama.cpp@0.7.0-dev (build 11803, commit a37cc4610) | Qwen3.8-27B-ctx4kQ4_K_M | 37.82tok/s | 2,401.3tok/s | 862ms | 26.1ms | 26.9ms |
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_mmtzel_i367Related benchmarks
- More Qwen3.8-27B-ctx4k 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_mmtzel_i367
- Fingerprint hash
- Public key
- m8z7LfcsRrMqsGxyX15NSYrFEL2VzFtJAlnApRQBhuY=
- Received
- 2026-10-22 04:32:06