Tracked topic
…MoE, quantization, and accessibility tools like Ollama and LM Studio have extended the lifespan of three generation old cards, and in the hands of users who are looking to complement their workflows…
…Qwen3 4B Instruct is a lightweight model that supports native tool calling, which is a non-negotiable requirement that rules out most general-purpose models. Without it, an LLM can "discuss" your…
…CoreWeave has deployed Kimi K2.6 on NVIDIA GB300 NVL72, combining NVFP4 quantization and EAGLE3 speculative decoding to maximize inference performance. Perplexity runs Qwen3 235B and post-trained Qwen3.5-397B-A17B…
…The way it handles tool integration, file edits, and permissions just feels more polished to me, and I've had better success with local models like Qwen3 Coder Next with Claude Code…
…AMD is going about it differently Unified platform with quantization AMD has been testing its latest Ryzen AI Max+ chipset using ROCm, Ollama, and Qwen 3.5 models. Because the CPU and…
…and Qwen3.6-27B local models in several popular LLM benchmarks. Running a 30B model at full precision locally normally requires over 55GB of memory. However, the 4-bit quantized version reduces…
…hits or turning down the quantization rate makes them a force to be reckoned with. And having tested GPT-OSS-20B, Gemma-4-26B-A4B , and Qwen3.6-35B-A3B with my…
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…Ollama's updated MLX engine now supports NVIDIA's model-optimized NVFP4 quantization format. Quantization reduces the memory required to run a model, but it also removes some information from the original…
…Tool calling that's baked into the architecture This model is great for practical uses One of the things that's held back local LLMs for agentic workflows is tool calling. Most…