LM Studio Boosts Local Language Model Performance by 25% with Qwen 3.5 Update
qwen
| Source: Mastodon | Original article
LM Studio boosts local LLM speeds by 25%. Qwen 3.5: 4B model now runs faster on computers.
LM Studio has announced a significant speed boost for local large language models (LLMs), claiming a 25% increase in speed for the Qwen 3.5: 4B model. This development is crucial as local LLMs are becoming increasingly practical for many developer workflows, with models in the 3B to 8B parameter range delivering quality that previously required 30B+ parameters.
The improved speed will enable users to get quicker answers from their local LLMs, making them more efficient and effective. This update is particularly notable given the recent advancements in local LLM tooling and model ecosystems, which have made running local LLMs a viable option. As reported earlier, local LLMs like gpt-oss, Qwen3.6, and Gemma4 can now be run locally on personal hardware, thanks to runtimes like Ollama and LM Studio.
As the local LLM landscape continues to evolve, it will be essential to watch how these developments impact the broader AI community. With LM Studio's GPU offloading feature and the introduction of Multi-Token Prediction (MTP) speculative decoding, users can expect even more significant speed boosts in the future. The next steps will likely involve further optimization and refinement of these technologies, potentially leading to widespread adoption of local LLMs in various industries.
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