AI-ML
Ollama v0.30.6
RESUMEN
New models - Gemma 4 QAT weights: the Gemma 4 family is now optimized with Quantization-Aware Training (QAT) to dramatically reduce memory requirements and maximize on-device performance. Look for the tags ending in `-qat`: - `gemma4:e2b-it-qat` - `gemma
Descripción Detallada
New models - Gemma 4 QAT weights: the Gemma 4 family is now optimized with Quantization-Aware Training (QAT) to dramatically reduce memory requirements and maximize on-device performance. Look for the tags ending in `-qat`: - `gemma4:e2b-it-qat` - `gemma4:e4b-it-qat` - `gemma4:12b-it-qat` - `gemma4:26b-a4b-it-qat` - `gemma4:31b-it-qat` What's Changed `ollama launch omp` now integrates with Oh My Pi, an AI coding agent with IDE integration MLX embedding layers now use NVFP4 global scale for improved quantization on Apple Silicon Full Changelog:
Explicación con IA
Genera un resumen en lenguaje claro de los cambios de este release.
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## What's Changed * Fixed an MLX Metal bug that could reduce output quality for NVFP4 models, particularly Laguna. **Full Changelog**: https://github.com/ollama/ollama/compare/v0.32.4...v0.32.5
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Ollama v0.32.4
## What's Changed - Support Laguna on Apple GPUs via the MLX engine - Quantize draft-model output heads at the requested type when creating speculative-decoding drafts. - Fixed Qwen3 MoE decoding for differently-quantized experts, plus faster packed gate/up projection (~4–9% on M5 Max). **Full
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