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delicious_apple

12 karma · joined May 21, 2026

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delicious_apple··on LFM2.5-24B-A2B: Built for fast on-device agents
I don't agree with that conclusion. I'm looking at the benchmarks page for LFM2.5-24B-A2B, and it appears to get a worse score on SWE-Bench-Verified (by a lot) when compared to Qwen 3.6 35B-A3B. It only clearly beats Qwen 3.6 35B on AutomationBench, ToolSandbox, and LiveClaw.

At least for my use cases, Qwen 3.6 35B-A3B appears better than this new release. An MoE for Qwen 3.8 would be even better than that!

delicious_apple··on Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
I'm currently running it on an RTX 3090 (street price ~$1000 USD) with a long context and getting pretty good performance.

Prefill: ~1000 tok/s

Decode: 75-100 tok/s

It'll be far faster on a 5090, but I find the above performance to be acceptable. I've seen some claims that it even works OK on an AMD RX 7900XT (~$500USD)

delicious_apple··on Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
I am running it on a single RTX 3090 (24GB VRAM).

Some folks on Reddit are having the same experience: https://www.reddit.com/r/LocalLLaMA/comments/1vkm42m/muse_gl...

It uses an order of magnitude less VRAM at longer contexts which is a huge advantage over Qwen 3.6 27B

delicious_apple··on Blog ran on Ubuntu 16.04 for 10 years. I migrated it to FreeBSD
You can always try openSUSE Slowroll (in beta), which is a rolling release that updates less frequently than Tumbleweed. It advertises better stability.

https://en.opensuse.org/Portal:Slowroll