Qwen3.8 Flash Next › NVIDIA RTX 5070 Ti
Qwen3.8 Flash Next on the NVIDIA RTX 5070 Ti
Qwen3.8 Flash Next runs at about 14.9 tokens/s on the NVIDIA RTX 5070 Ti (measured, UD-Q4_K_XL, CUDA, single-stream llama-server decode, part of the model on CPU).
Best measured: 14.9 tokens/s generation (UD-Q4_K_XL, CUDA). The source gives no prompt-processing figure.
For comparison, our size-scaling estimate for this combination is 92.4 tok/s.
Every run
| Quant | Backend | Generate tok/s | Prompt tok/s | Test | Build / by / notes | Source |
|---|---|---|---|---|---|---|
| UD-Q4_K_XL | CUDA | 14.9 | – | decode, llama-server, 25K prompt | b10715 Machino Windows, 128 GB RAM, --n-cpu-moe 48 (experts in system RAM), 25,229-token prompt.; model file is larger than this card's VRAM, so part of it ran on the CPU/system RAM | unsloth Qwen3.8-Flash-Next GGUF speed thread (Hugging Face) |
tg128 = generating 128 tokens; pp512 = reading a 512-token prompt (llama-bench). LocalScore averages several prompt and output lengths, so its numbers run lower than tg128. "decode, llama-server" = single-stream generation speed measured against a running llama-server (no speculative decoding).
Doesn't fit in this card's VRAM
Part of this model ran on the CPU here. A rented 48-80 GB GPU keeps it all in VRAM.
Rent a bigger GPU on RunPodAffiliate link: if you sign up, RigBench may earn a referral credit. It never affects rankings or numbers.
All results for the NVIDIA RTX 5070 Ti · Qwen3.8 Flash Next on other hardware
Embed this result
HTML
<a href="https://rigbench.pages.dev/model/qwen3-8-flash-next/on/nvidia-rtx-5070-ti/"><img src="https://rigbench.pages.dev/badge/qwen3-8-flash-next--nvidia-rtx-5070-ti.svg" alt="Qwen3.8 Flash Next · NVIDIA RTX 5070 Ti: 14.9 tok/s (UD-Q4_K_XL, measured)"></a>
Markdown (GitHub README, forums)
[](https://rigbench.pages.dev/model/qwen3-8-flash-next/on/nvidia-rtx-5070-ti/)