Type a name, or just describe what you need. Results blend keyword and meaning-based search. 80 matches, each with an EU availability status.
Model · Alibaba
Alibaba's open-weights 2.4T-parameter MoE language model (95B active) from the Qwen3.8 family, with a hosted Max version.
Model · Z.ai
Z.ai's open-weights 753B MoE language model, a post-trained GLM-5.2 aimed at coding, agentic tasks and cybersecurity.
Model · Meta
Meta's open-weights 30B dense model for local agents, tuned for tool use and long tasks, Apache 2.0 licensed.
Model · Thinking Machines
Open-weights multimodal MoE model (276B total, 12B active) from Thinking Machines; text, image and audio in, text out.
Model · Rednote
Open MoE language model from Rednote (Xiaohongshu) with 208B total and 16B active parameters.
Model · Reflection AI
Reflection AI's 501B-parameter open-weight mixture-of-experts model for coding, reasoning and agentic workloads.
Model · MiniMax
Open-weights native multimodal MoE model from MiniMax, ~428B parameters (~23B active) with 1M-token context.
Model · Accio Lab
Open-weights 35B MoE (3B active) agentic model from Accio Lab, post-trained from Qwen3.6-35B-A3B.
Model · Baidu
Baidu's open-weights 280B-parameter sparse MoE base model (14B active) with 1M-token context, released pre-post-training.
Compact 27B-parameter model from Alibaba's Qwen family, runnable locally on a single high-end consumer GPU.
Model
Open 7.39B dense model for math reasoning and agentic search, with a 256K context and the full training pipeline released.
Model · Recursive Intelligence
Dense 65B open-weight language model from Ricursive Intelligence, trained for agentic coding with up to 1M context.
35B Mixture-of-Experts open-weights model from InternScience for long-horizon agentic search, engineering and tool use.
Model · NVIDIA
NVIDIA's open-weight 30B mixture-of-experts model with 1M-token context, aimed at long-running agent workloads.
Model · Sarvam AI
Open-weights decision model on Sarvam-105B that returns probabilities for fixed answer options in one forward pass.
Model · Perplexity
Two open-sourced Perplexity decision models, at 4B and 27B parameters, announced by the company.
Model · Google
Google's open-weights 12B encoder-free multimodal model in the Gemma 4 family, taking text, image and audio input.
Google's open-weights 12B multimodal (text and image input) instruction-tuned model from the Gemma 3 family.
Family of four open MoE language models (19B to 280B), reportedly pruned from DeepSeek and Qwen bases.
Model · Alpha Innovator
35B mixture-of-experts open-weights agentic model for engineering, long-horizon search and scientific research.
Model · Nanbeige
33B dense open-weights LLM from Nanbeige, tuned for agentic coding and professional cowork tasks.
Alibaba's Qwen coding-specialist language model, available as open weights for local and hosted use.
Model · inclusionAI
Open-weights 124B MoE healthcare model (5.1B active) from inclusionAI, specialized from Ling-3.0-flash.
Model · MemTensor
Open-weights memory foundation model from MemTensor with a fixed-size persistent memory state, built on Qwen3.6-35B-A3B.
