Can 2x Tesla V100 32GB run Qwen3.8 Flash-Next?
Probably only partly: the weights are larger than its memory, so part of the model likely ran from system RAM. Measured 121 tok/s generation with part of the model offloaded to system RAM (bnk v0.3.1, decode at 4K context, IQ3_S; source).
Every measured result for Qwen3.8 Flash-Next on 2x Tesla V100 32GB
| Build | Quant / setup | Engine | tok/s | |
|---|---|---|---|---|
| Dual Tesla V100 32 GB on EPYC 7402 (bnk engine) | IQ3_S | bnk v0.3.1, decode at 4K context | 121 CPU offload | source |
| Dual Tesla V100 32 GB on EPYC 7402 (bnk engine) | FP4-Local | bnk v0.3.1, decode at 4K context | 114 CPU offload | source |
Memory: 2x Tesla V100 32GB has 64 GB. Qwen3.8 Flash-Next weights are about 110.1 GB at Q4_K_M (180B params × 4.89 bits ÷ 8, before context/KV cache). Arithmetic, not a measurement; long contexts need more. Check other quants in the VRAM calculator.
Speeds are decode (generation) tokens/sec as reported by each source; quant, engine and context differ, so small gaps are noise.
All measured speeds for Qwen3.8 Flash-Next: best home rig for Qwen3.8 Flash-Next.
Qwen3.8 Flash-Next on other hardware: 2x Intel Arc Pro B70 · 2x RTX 5070 Ti · 2x RTX 5080 · 2x RTX PRO 4000 Blackwell · DGX Spark (GB10) · RTX 5090
Other models measured on 2x Tesla V100 32GB: DeepSeek V4.1 Flash · Qwen3.8 27B
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