Introducing Mellum2: A 12B Mixture-of-Experts Model by JetBrains

• Mellum2 is a 12B-parameter Mixture-of-Experts model trained from scratch on natural language and code.
• The model activates only 2.5B parameters per token, making it efficient for high-throughput, low-latency inference. Mellum2 is can be used for routing, RAG, summarization, sub-agents, high-throughput coding features, and private deployments.
• It is released under the Apache 2.0 license.
• Compared with similar-sized models, Mellum2 delivers competitive benchmark performance while achieving more than 2x faster inference.
• Download the model on Hugging Face: https://huggingface.co/collections/JetBrains/mellum-2
• For architecture details, training setup, benchmarks, and evaluation methodology, read the full technical report: https://arxiv.org/pdf/2605.31268

Today we’re releasing Mellum2, an open Mixture-of-Experts model optimized for low-latency text-and-code workloads. Mellum originally started as a code completion model. With Mellum2, we extend that foundation to a broader set of natural language and software engineering tasks while keeping the model focused on efficient inference and deployability. Modern AI systems increasingly rely on multiple model calls: routing, retrieval, summarization, planning, validation, and tool use. Many of these operations are latency-sensitive and do not require the largest available model. Mellum2 targets these workloads.

Benchmark highlights

In our technical report, we evaluate Mellum2 across code generation, reasoning, science, and math benchmarks. Mellum2 is competitive with similarly sized open models while delivering more than 2x faster inference, making it suitable for high-throughput production workloads. Model architecture Mellum2 is a Mixture-of-Experts model:

Model	Total parameters	Active parameters per token	Modality	License
Mellum2	12B	2.5B	Text and code	Apache 2.0