Follow AI Builders — Not Influencers
RT Jake Broekhuizen The product of some of the work the LangChain Labs team has been up to recently 📌 You can read more about it here - https://www.langchain.com/blog/building-a-100x-cheaper-trace-judge-with-fireworks - and try it out for yourself by signing up below
We are starting to role out our Trace Judge model to early partners today Designed to detect errors in agent trajectories at 1/100th of the cost compared to closed models If interested in early access, sign up on the form below: https://airtable.com/appWdRBlSecNOgErA/pagAEfUlHu4F35opm/form
We are starting to role out our Trace Judge model to early partners today Designed to detect errors in agent trajectories at 1/100th of the cost compared to closed models If interested in early access, sign up on the form below: https://airtable.com/appWdRBlSecNOgErA/pagAEfUlHu4F35opm/form
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 coo...
