DeepReinforce 新出的开源编码模型，基于 Gemma 4 和 Qwen 3.5，在代理编码任务上表现不错，LM Studio 就能跑，值得试试。
DeepReinforce 发布 Ornith-1.0，一款 MIT 许可的开源模型，基于 Gemma 4 和 Qwen 3.5 预训练。提供 9B Dense、31B Dense、35B MoE 和 397B MoE 四种规格。在编码基准上达到同尺寸开源模型 SOTA。作者在 LM Studio 上测试 35B Q4_K_M GGUF 版本，能流畅运行代理工具调用并处理代码定位任务。
Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding
Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding This is an interesting new open weights (MIT licensed) model, the first model release from DeepReinforce. [...] with variants including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Built on top of pretrained Gemma 4 and Qwen 3.5, it achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks. As far as I can tell the licenses of those underlying models is compatible with being used in this way - Gemma 4 is Apache 2.0 licensed (and not bound by the janky additional Gemma Terms of Use that afflicted the previous Gemma models) and Qwen 3.5 is Apache 2.0 licensed as well. I've been running the model using LM Studio and the ornith-1.0-35b-Q4_K_M.gguf (20GB) GGUF, hooked up to Pi . Initial impressions are very good - it seems to be able to run the agent harness over many tool calls in a proficient way. Here's a terminal session where I asked it to "find the code that decodes the actor cookie" and then "find the code that opens the insert dialog when thebutton is clicked" against a Datasette checkout, which it handled with ease. I also had it draw this pelican , which came out at 103 tokens/second: It's a little bit mangled but the pelican is clearly a pelican. I couldn't find much information about DeepReinforce themselves. The earliest paper I could find from the was CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning from June 2025. Tags: ai , generative-ai , local-llms , llms , qwen , pelican-riding-a-bicycle , gemma , llm-release , lm-studio