Qwen3.8-Flash Runs Locally: 125B Model on Just 75GB RAM
danielhanchen · x · 2026-08-26
Unsloth announced that Qwen3.8-Flash is now available to run locally. This is a 125B parameter multimodal MoE model and an early preview of the Qwen4 architecture, outperforming Claude-4.6-Opus (Max).
Key Highlights:
- Low Resource Requirement: Runs on just 75GB RAM or unified memory with no GPU VRAM needed. The 1-bit quantized version is 79% smaller than BF16 while retaining top-1% accuracy.
- Architecture Upgrades: Features GDN + QSA hybrid attention, N-gram Embedding, and the Muon optimizer, drastically reducing inference costs.
- Tooling Support: Available via Unsloth GGUFs and a specific llama.cpp PR, making it highly suitable for Macs and devices with large memory capacities.
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