vLLM v0.25.0 ships Model Runner V2, enhancing local LLM inference

The vLLM project has released version 0.25.0, featuring Model Runner V2 as the default for dense models, which enhances quantization support for more efficient local LLM inference. This update aims to improve throughput and latency, making it easier to run complex open-weight models on consumer hardware. Additionally, Ollama v0.32.5 has been released to fix a bug affecting output quality for NVFP4 models on Apple Silicon, ensuring better reliability for local inference on macOS devices. AI

IMPACT Enhances efficiency and accessibility for running large language models locally on consumer hardware.

RANK_REASON This cluster reports on software releases for LLM inference tools, not a frontier model release.

Read on dev.to — LLM tag →

• AMD
• Apple Silicon
• KataGo
• Model Runner V2
• NVFP4
• Ollama
• ROCm
• Transformer
• vLLM

• model release
• infra

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