Qwen-3.8-27B, Nemotron-3.5-Lightning-30B-A3B, Ornith-1.5-35B-A3B, Muse-Glimmer-30B oQ8e comparison

Reddit r/LocalLLaMA Models

Summary

A comparison of multiple AI models including Qwen, Nemotron, Ornith, and Muse-Glimmer on benchmarks, with Ornith performing well and TielCoder showing potential in coding tasks.

Ornith does really well. TielCoder (https://llm-bench.io/benchmarks/cmt7kp2zj002r01lcmpchvlko) might be even a bit better in coding. Will give it a try soon. Details of the comparison see here: https://llm-bench.io/compare/runs?runs=cmt6ecf8g000001p45vwzux53%2Ccmt6ergk5000701p41hqdyy78%2Ccmt6f2oob000e01p49o9592cb%2Ccmt6fqddm000l01p4l1vm7skd
Original Article

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Local benchmarks with a RTX 3090 - Qwen3.6 27b vs Ornith

Reddit r/LocalLLaMA

User runs local benchmarks comparing Qwen3.6 27b, Gemma4 26B, and Ornith1.0 35B on an RTX 3090 using inspect-ai. Results show Qwen leading in knowledge and coding, while Ornith is competitive in grounding and recall.

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Ornith-1.5-35B-A3B is a mixture-of-experts AI model that activates only 3B parameters per token and outperforms similar-sized models like Qwen and Gemma in coding and agentic benchmarks.