JetBrains releases Mellum2.1 coding model
AI summary
JetBrains launched Mellum2.1, keeping Mellum2's 12B mixture-of-experts architecture with 2.5B active parameters and the Apache 2.0 license, and focusing the upgrade on agentic coding. JetBrains says reinforcement learning was expanded from a short post-training step into the main training stage, letting the model explore codebases, edit files, identify root causes of failing tests and draft and verify fixes. The model is available on Hugging Face, with GGUF builds for llama.cpp, Ollama and LM Studio and a vLLM MTP speculative-decoding component promised later.
In-depth insight
It adds another open-weight option for coding agents that can run on local or self-hosted infrastructure, and the vendor-reported throughput edge could cut inference costs at scale.