Benchmark result
AtomicChat/Qwen3.8-Flash-Next-GGUF on NVIDIA GeForce RTX 5090 — 39.7 tok/s
Measured with vLLM on August 30, 2026.
What the model built
Open full screen →The coding scenario asks for a playable game in a single HTML file. This is exactly what the model returned, unedited; the frame only adds a line that tells this page how tall it is.
How this run compares
2nd fastest of 3 runs of this model on NVIDIA GeForce RTX 5090 · median 39.7 tok/s.
sort
- 143.4tok/s87.2vLLM
- 239.7tok/s86.9vLLMthis run
- 334.9tok/s88.1vLLM
AtomicChat/Qwen3.8-Flash-Next-GGUF on other hardware
Reproduce this run
toolvLLM
modelAtomicChat/Qwen3.8-Flash-Next-GGUF
context65,536
clientv0.4.46+97
Set those in vLLM, then:
llm-benchmark benchmark --model "AtomicChat/Qwen3.8-Flash-Next-GGUF" --tool "vLLM"The client prompts for context length and thinking mode, and for the KV cache dtype on Unsloth Studio. Sampling is left at the model default — the values above are what the tool reported using, not overrides the client sent.