JetBrains Introduces Mellum2: A 12B Mixture-of-Experts Model for Code and Text

ArticleNikita PavlichenkoAnnouncement

JetBrains has released Mellum2, a 12B-parameter Mixture-of-Experts model trained from scratch on natural language and code. Activating only 2.5B parameters per token and published under the Apache 2.0 license, it is designed for low-latency, high-throughput developer and AI workloads.

Key points

  1. Mellum2 features 12B total parameters while activating only 2.5B parameters per token.
  2. The model specializes strictly in text and code, avoiding multimodal overhead.
  3. JetBrains reports competitive benchmark scores alongside more than 2x faster inference compared to similar-sized models.
  4. Key use cases include orchestration and routing, RAG context compression, sub-agents, and self-hosted private deployments.
  5. Model weights are published on Hugging Face under the Apache 2.0 license.

Why it matters

Production AI systems are shifting away from monolithic architectures toward composite setups. Fast, well-scoped open-source models dramatically reduce inference latency and serving costs for high-frequency tasks, while also enabling secure local deployment for proprietary codebases.

Analysis

JetBrains intentionally scopes Mellum2 as a 'focal' model for intermediate tasks within larger agent or developer workflows. By combining an MoE architecture with a strict focus on code and text, the model achieves the low latency required for real-time orchestration without sacrificing domain-specific capability.

Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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