LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
We introduce Olmo 3, a new family of 7B and 32B models both Instruct and Think variants. Long chain-of-thought thinking improves reasoning tasks like math and coding.
We introduce Olmo 3, a new family of 7B and 32B models both Instruct and Think variants. Long chain-of-thought thinking improves reasoning tasks like math and coding.
Model Summary: Granite‑4.1‑8B‑Base is a decoder‑only language model with long‑context capabilities, designed to support a broad range of text‑to‑text generation tasks. In addition to standard generation, it supports Fill‑in‑the‑Middle (FIM) code completion through specialized pre…
Model Card for Olmo-3.1-32B-Instruct-DPO
We introduce Olmo 3, a new family of 7B and 32B models both Instruct and Think variants. Long chain-of-thought thinking improves reasoning tasks like math and coding.
LFM2.5 is a new family of hybrid models designed for on-device deployment . It builds on the LFM2 architecture with extended pre-training and reinforcement learning.
Molmo2 is a family of open vision-language models developed by the Allen Institute for AI (Ai2) that support image, video and multi-image understanding and grounding. Molmo2 models are trained on publicly available third party datasets as referenced in our technical report and Mo…
📣 Update [10-07-2025]: Added a default system prompt to the chat template to guide the model towards more professional, accurate, and safe responses.
📣 Update [10-07-2025]: Added a default system prompt to the chat template to guide the model towards more professional, accurate, and safe responses.
LFM2.5‑VL-1.6B is Liquid AI's refreshed version of the first vision-language model, LFM2-VL-1.6B, built on an updated backbone LFM2.5-1.2B-Base and tuned for stronger real-world performance. Find more about LFM2.5 family of models in our blog post.
Model Summary: Granite-4.0-350M is a lightweight instruct model finetuned from Granite-4.0-350M-Base using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets. This model is developed using a diverse set of techniq…
LFM2.5 is a new family of hybrid models designed for on-device deployment . It builds on the LFM2 architecture with extended pre-training and reinforcement learning.