fix review findings and additional clean up#116
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mlabonne
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Jul 11, 2026
| | Qwen3-4B/8B, Llama-3.1-8B, Gemma-3-12B | [LFM2.5-8B-A1B](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B) | MoE with 8B total and 1.5B active parameters. | | ||
| | Qwen3-14B/32B and larger dense models | [LFM2-24B-A2B](https://huggingface.co/LiquidAI/LFM2-24B-A2B) | 24B total and roughly 2.3B active parameters. | | ||
| | Qwen3 thinking mode or DeepSeek distills | [LFM2.5-1.2B-Thinking](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking) | Reasoning traces at 1.2B. | | ||
| | Qwen3-0.6B, Llama-3.2-1B, Gemma-3-270M/1B | [LFM2.5-230M](https://huggingface.co/LiquidAI/LFM2.5-230M) or [LFM2.5-350M](https://huggingface.co/LiquidAI/LFM2.5-350M) | Smallest text models for classification, extraction, routing, and tight memory budgets. | |
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I noticed that we're talking about Qwen3 and Gemma 3 instead of Qwen3.5 and Gemma 4 everywhere. We should probably either update it when there's a clear replacement or have both when there's none (particularly true for Gemma 4).
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to reduce maintenance efforts for the future, i decided to remove all direct model IDs and replace them with more generic categories.
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lfm2parser and native Pythonic tool-call format. (confirmed its calledlfm2parser