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My models on the Intel Low-Bit LLM Leaderboard
Figured I'd share where my quantized models landed on Intel/low_bit_open_llm_leaderboard since I hadn't posted about it yet.
FlameF0X/Qwen3-4B-Distilled-Claude-4.6 (NVFP4 and MXFP4) sit at ranks 23 and 24 with 62.68% and 61.18% average, right below the base Qwen3-4B. Not bad considering they were distilled from Claude 4.6 rather than trained from scratch.
FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6 and FlameF0X/LFM2.5-1.2B-Thinking-CodeX land around rank 47-49, competitive with MiniCPM5-1B and the Qwen3 sub-1B models despite being a larger base architecture.
The funny one is FlameF0X/Qwen2-0.2B-pt and FlameF0X/Qwen2-0.2B-it. They're not properly trained — genuinely undertrained, basically undefined — and they still beat openai/gpt-oss-20b at rank 66. The 20B model. Not sure what that says but it's something.
FlameF0X/LFM2-Research is at the bottom of my lineup but it's a research artifact, not meant to be competitive.
Chart below showing my models vs nearby competitors, with size vs performance on the left.
Chart made by Claude
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