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Gemma 4 12B

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Headlines · 3

  1. webAI Releases TwIL-8B Reasoning Model

    webAI released the TwIL-8B reasoning model under a non-commercial license. Built on IBM Granite-4.2-8B, it is optimized for mathematics, coding, and instruction-following workloads. According to webAI, TwIL-8B achieved the best results among the compared models on MATH-500, AIME 2025, and LiveCodeBench, while matching Gemma 4 12B on IFBench. webAI also said the model reaches 88% to 93% of frontier-model reasoning capability in its areas of strength and can reduce AI usage costs in many cases. IT之家 noted that the model has limited knowledge and is not general-purpose.

    IT之家 AI · 🔥 0
  2. Developer prunes Gemma 4 26B-A4B to 15% for on-device use

    A Reddit developer reported pruning the MoE model Gemma 4 26B-A4B to 15% of its original size by retaining eight experts per layer. Because the model normally selects eight experts per token, this makes routing deterministic and produces a dense 3.81B-parameter model, or 2.75 GB in Q4_K_M. The pruned model achieved 92% agreement with the original on one narrow classification task, compared with 90% agreement between the 12B and 26B models on the same samples. On the developer's Mac, it ran at 79 tokens per second using 3.8 GB of memory, roughly twice the speed and half the memory of the 12B model. The developer said it is not a general-purpose model and that knowledge-dependent tasks suffer.

    r/LocalLLaMA · 🔥 0
  3. Claude rewrites eight Gemma 4 neurons to adjust Italian tense selection

    A Reddit author reports using Claude Opus 5.5 to rewrite eight MLP neurons in Gemma 4 12B, creating a context-sensitive switch for Italian tense translation without gradients or conventional training. In the author's tests, the edit left 5% and 16% of sentences in the original form across two tests, compared with 4% and 2% for a system-prompt preference. However, the prompt broke 49 control cases, compared with two for the edit, while the edit left 182 of 200 unrelated translations unchanged versus 82 for the prompt. The experiment covered one model and one Italian construction; two of three runs succeeded, while the third crashed because of the author's harness.

    r/LocalLLaMA · 🔥 0

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