Qwen3.8-Flash-Next
Qwen3.8-Flash-Next loads in 123 GB at IQ1_S and is comfortable from 192 GB of memory, Macs included from the Mac Studio M5 Ultra 256GB. Below: the full memory math, the cheapest card that runs it well, and the fastest machine we track.
PARAMETERS
125B (6B active)
FORMAT
IQ1_S
MIN MEMORY
192 GB
BEST FOR
Agentic coding, Reasoning, Multimodal
Memory math
Weights (IQ1_S)
123 GB
+ KV cache (16k)
~6.0 GB
Total at 16k
~129.0 GB
Comfortable from
192 GB
KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).
Hardware snapshot
Cheapest GPU
—
no consumer fit
More Qwen models
Qwen3.7-PlusQwen2.5 0.5B InstructQwen3.5 0.8B InstructQwen2.5 1.5B InstructQwen3.5 2B InstructQwen2.5 3B InstructQwen3.5 4B InstructQwen2.5 7B InstructQwen2.5 Coder 7BQwen3 8BQwen3.5 9B InstructQwen2.5 14B InstructQwen2.5 Coder 14BQwen3 14BQwen3.5 27B InstructQwen3.6 27BQwen3.8 27BQwen3 30BQwen3 30B (Q8)Qwen3.5 35B-A3B InstructQwen3.6 35B-A3BQwen3-Next 80B-A3BQwen3.5 122B-A10B InstructQwen3 235B A22B
Frequently asked questions
How much memory does Qwen3.8-Flash-Next need?
123 GB for the IQ1_S weights, plus ~6.0 GB of KV-cache at 16k context — about 129.0 GB total. Comfortable from 192 GB of VRAM or unified memory.
Does Qwen3.8-Flash-Next run on a Mac?
Yes — from the Mac Studio M5 Ultra 256GB (~32 tok/s est.). Unified memory means the RAM budget is the only limit.
What is the cheapest GPU for Qwen3.8-Flash-Next?
No tracked consumer GPU runs Qwen3.8-Flash-Next comfortably.
Cite this page
ModelFit: Qwen3.8-Flash-Next — specs, memory math and hardware verdicts. https://modelfit.io/models/qwen3.8-flash-next/ (dataset updated 2026-09-03, CC BY 4.0).