T
traeai
Sign in

产品

LM Studio

别名:lm-studio

一个图形界面工具,用于本地运行和比较大语言模型。

已跟踪 4 条高相关材料

TraeAI 观察

相关材料

已收录 4 条与 LM Studio 相关的内容,按评分排序。

Introducing Gemma 4 12B: a unified, encoder-free multimodal model

Introducing Gemma 4 12B: a unified, encoder-free multimodal model

The Keyword (blog.google)693 字 (约 3 分钟)
87

Gemma 4 12B is a unified, encoder-free multimodal model bringing high-performance multimodal intelligence to your laptop. It matches the performance of our 26B MoE at less than half the memory footprint, supports native audio inputs, and runs locally on 16GB VRAM hardware with low-latency multi-step reasoning.

入选理由:Gemma 4 12B 性能接近 26B MoE,内存仅其一半,适合在 16GB VRAM 现代本机运行。

FeaturedArticle#Gemma 4#12B#multimodal#unified architecture#encoder-free英文
How to Run LLMs Locally (Great For Learning and Privacy)

How to Run LLMs Locally (Great For Learning and Privacy)

ByteByteGo1316 字 (约 6 分钟)
85

本地运行大语言模型(LLMs)可通过 llama.cpp、Ollama 和 LM Studio 等工具实现,兼顾隐私与学习。

入选理由:使用 llama.cpp 可在消费级硬件上运行大型模型,支持 4-bit 量化。

FeaturedVideo#LLM#本地运行#AI#量化#Ollama英文
Zed + Gemma-4 12B & Qwen-3.6: HOW IS THIS POSSIBLE?! THIS IS CRAZY!

Zed + Gemma-4 12B & Qwen-3.6: HOW IS THIS POSSIBLE?! THIS IS CRAZY!

AICodeKing2235 字 (约 9 分钟)
85

Zed now supports direct use of local AI models like Gemma-4 12B and Qwen-3.6 in the editor, enhancing privacy and experimentation efficiency.

入选理由:Zed支持通过LM Studio/Ollama/llama.cpp集成本地模型

FeaturedVideo#AI model#local deployment#Zed editor英文
Hacker News Best 图标

Running local models on an M4 with 24GB memory

Hacker News Best1675 字 (约 7 分钟)
85

Running Qwen 3.5-9B (q4_k_s quantized) on an M4 MacBook with 24GB RAM achieves ~40 tokens/sec, supports 128K context and tool use for local development.

入选理由:Qwen 3.5-9B (q4_k_s) 在M4 Mac上以40 tokens/秒速度运行,支持128K上下文和工具使用

FeaturedArticle#LLM#local inference#M4#Qwen#LM Studio英文

跨材料问答 · LM Studio

回答基于:LM Studio 相关 4 条材料
    0 / 500

    AI may generate inaccurate information. Please verify important content.