The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware.
Building upon Mistral Small 3, Mistral Small 3.1 (2503) adds state-of-the-art vision understanding and enhances long context capabilities up to 128k tokens without compromising text performance.
Meta's latest open model built for always-on local agents. 30B parameters, licensed under Apache 2.0 and runs on a single GPU — tuned for tool use, long tasks, and failure recovery.
North Mini Code is Cohere's first model for developers — a 30B Mixture-of-Experts model with 3B active parameters, built for agentic software engineering.
Xiaomi's efficiency-balanced MiMo-V2.6 checkpoint, with 309B total parameters, 15B active, omnimodal input, and a 1M token context.
As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency.
MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension.
Mistral Medium 3.5 is the first flagship model of Mistral AI that merged instruction-following, reasoning, and coding in a single set of 128B weights.
An update to Mistral Small that improves on function calling, instruction following, and less repetition errors.
The IBM Granite 1B and 3B models are long-context mixture of experts (MoE) Granite models from IBM designed for low latency usage.
Mistral Small 3 sets a new benchmark in the “small” Large Language Models category below 70B.
A general-purpose model ranging from 3 billion parameters to 70 billion, suitable for entry-level hardware.
The IBM Granite 1B and 3B models are the first mixture of experts (MoE) Granite models from IBM designed for low latency usage.
A model from NVIDIA based on Llama 3 that excels at conversational question answering (QA) and retrieval-augmented generation (RAG).
The IBM Granite Embedding 30M and 278M models models are text-only dense biencoder embedding models, with 30M available in English only and 278M serving multilingual use cases.
Moka-AI Massive Mixed Embedding
Embedding
embedding