Qwen3.8-27B-ctx16k on RTX 4090 (24GB)
MeasuredOn 2026-10-22, Qwen3.8-27B-ctx16k Q4_K_M ran at 43.4 tok/s (chat-short) on an RTX 4090 (24GB) with llama.cpp. Run r_cthpfm82n1r.
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-ctx16kQ4_K_M | 43.38tok/s | 472.6tok/s | 326ms | 22.9ms | 23.2ms |
| chat-long | llama.cpp@0.7.0-dev (build 11803, commit a37cc4610) | Qwen3.8-27B-ctx16kQ4_K_M | 42.94tok/s | 1,958.6tok/s | 1,646ms | 23.2ms | 23.5ms |
| concurrent-decode | llama.cpp@0.7.0-dev (build 11803, commit a37cc4610) | Qwen3.8-27B-ctx16kQ4_K_M | 43.28tok/s | — | — | 23.0ms | 23.4ms |
| agent-trace | llama.cpp@0.7.0-dev (build 11803, commit a37cc4610) | Qwen3.8-27B-ctx16kQ4_K_M | 42.55tok/s | 3,858.7tok/s | 583ms | 23.2ms | 23.6ms |
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_cthpfm82n1rRelated benchmarks
- More Qwen3.8-27B-ctx16k benchmarks — every backend and rig that has run this model.
- More RTX 4090 (24GB) LLM benchmarks — every model measured on this hardware.
Provenance
- Run ID
- r_cthpfm82n1r
- Fingerprint hash
- Public key
- diBAO7sZfa3K4rRcDobL7mSUOwaqCanvkTCsjvJbdM8=
- Received
- 2026-10-22 04:15:28