Model benchmarks
Qwen3.8-27B-GPTQ-W4A16 local LLM performance
As of August 2026, Qwen3.8-27B-GPTQ-W4A16 runs at up to 47.7 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
vLLM
Model size
27B
Peak speed
47.7 tok/s
Average speed
47.1 tok/s
Min memory
n/a
Max context
8,623 tokens
Best quality
87.4
Benchmark runs
2
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-GPTQ-W4A16 has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XT/7900 XTX/7900M | vLLM | — | 47.7 tok/s | 47.1 tok/s | n/a | 8,623 tokens | 75.4 | 2 |
Frequently asked questions
- How fast is Qwen3.8-27B-GPTQ-W4A16 for local inference?
- Across 2 community benchmark runs, Qwen3.8-27B-GPTQ-W4A16 reaches up to 47.7 tok/s and averages 47.1 tok/s, with the fastest results on AMD Radeon RX 7900 XT/7900 XTX/7900M.
- How much memory does Qwen3.8-27B-GPTQ-W4A16 need?
- The leanest observed configuration used about n/a of memory.
- Which tools have been used to run Qwen3.8-27B-GPTQ-W4A16?
- Benchmarks were submitted using vLLM. Results are community-contributed and updated as new runs arrive.