github ROCm/FastFlowLM v1.0.2
🚀 FastFlowLM v1.0.2 — Faster Qwen3.5 & Qwen3.6-MoE

6 hours ago

This release brings a solid decoding and prefill speed boost across the entire Qwen3.5 family and Qwen3.6-MoE, plus a heads-up on a required weight update.


📥 Weights Update Required

Models in this release are quantized by FLM itself. If you're upgrading to v1.0.2, you'll need to re-download weights for the Qwen3.5 family and Qwen3.6-MoE — existing local copies from prior versions are not compatible.

flm pull qwen3.5:0.8b
flm pull qwen3.5:2b
flm pull qwen3.5:4b
flm pull qwen3.5:9b
flm pull qwen3.6-moe:35b-a3b

⚡ Performance Boost: Qwen3.5 Family & Qwen3.6-MoE

Both prefill and decoding throughput have been improved across all context lengths (1k–32k) for Qwen3.5 (0.8B, 2B, 4B, 9B) and Qwen3.6-MoE (35B-A3B).

Model Decoding Gain (avg / peak) Prefill Gain (avg / peak)
Qwen3.5 0.8B +9.5% / +14.5% +34.8% / +44.3%
Qwen3.5 2B +10.2% / +11.8% +27.2% / +33.3%
Qwen3.5 4B +11.5% / +13.1% +31.5% / +37.4%
Qwen3.5 9B +12.0% / +13.0% +25.5% / +29.2%
Qwen3.6-MoE 35B-A3B +11.4% / +13.0% +15.9% / +19.7%

Gains are largest on smaller models and at mid-to-long context lengths, with prefill benefiting more than decoding across the board.


🌟 Summary

Highlight
📥 Weights update required for Qwen3.5 family and Qwen3.6-MoE — re-pull models before running v1.0.2
Qwen3.5 family (0.8B/2B/4B/9B): up to +14.5% decoding and +44.3% prefill throughput
Qwen3.6-MoE 35B-A3B: up to +13.0% decoding and +19.7% prefill throughput

Thanks for your support — see you in the next one! 🚀

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