github ROCm/FastFlowLM v0.9.46
🚀 FastFlowLM v0.9.46 — We're Moving!

10 days ago

🏠 FastFlowLM is Now an Official AMD Project

🎉 FastFlowLM has joined the ROCm organization and is now officially maintained by AMD. This is the last release under FastFlowLM/FastFlowLM — starting from v1.0.0, everything moves to ROCm/FastFlowLM. Please update your bookmarks, forks, and remotes accordingly. See you there!


🌐 ModelScope Support

Models are pulled from HuggingFace by default. You can now opt into ModelScope as an alternative source with a single flag.

Pull a model from ModelScope:

flm pull llama3.2:1b --modelscope 1

Auto-pull from ModelScope in CLI mode:

flm run llama3.2:1b --modelscope 1

Auto-pull from ModelScope in server mode:

flm serve --modelscope 1

Check the compatibility of your local model with ModelScope:

flm check llama3.2:1b --modelscope 1

🖼️ More Image Resize Levels for Qwen-VL Models

Fine-grained control over input image resolution is now available via the -r flag:

flm serve -r <img-pre-resize-level>
Level Resolution
0 Original size
1 Height = 480
2 Height = 720
3 Height = 1080
4 Height = 1440
5 Height = 2160
6 Height = 2880
7 Height = 3240
8 Height = 4320

⚡ Speed Improvements for Qwen3.6-MoE

Both prefill and decoding throughput have been improved for Qwen3.6-MoE across all context lengths.

Decoding throughput (tokens/s):

Context Old New Gain
1k 12.41 13.65 +9.99%
2k 12.26 13.41 +9.38%
4k 11.96 13.09 +9.45%
8k 11.38 12.51 +9.93%
16k 10.40 11.24 +8.08%
32k 8.88 9.51 +7.09%

Prefill throughput (tokens/s):

Context Old New Gain
1k 75.18 78.98 +5.05%
2k 109.85 118.04 +7.46%
4k 150.93 156.43 +3.64%
8k 181.56 197.93 +9.02%
16k 214.46 218.84 +2.04%
32k 219.72 221.96 +1.02%

🌟 Summary

Highlight
🏠 FastFlowLM is now an official AMD project — repo moved to ROCm/FastFlowLM
🌐 ModelScope support: pull, serve, and check model compatibility
🖼️ 9-level image resize control for Qwen-VL models
Up to ~+10% decoding and ~+9% prefill speedup for Qwen3.6-MoE

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