LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
Building the Next Generation of Open-Source and Bilingual LLMs
Falcon-7B-Instruct is a 7B parameters causal decoder-only model built by TII based on Falcon-7B and finetuned on a mixture of chat/instruct datasets. It is made available under the Apache 2.0 license.
Join Our 💬 WeChat 🧩 Discord community. MiniMax Agent ⚡️ API MCP MiniMax Website 🤗 Hugging Face 🐙 GitHub 🤖️ ModelScope 📄 License: Modified-MIT
The GLM family welcomes new members, the GLM-4-32B-0414 series models, featuring 32 billion parameters. Its performance is comparable to OpenAI’s GPT series and DeepSeek’s V3/R1 series. It also supports very user-friendly local deployment features. GLM-4-32B-Base-0414 was pre-tra…
[!Note] This is an improved version of Kimi-VL-A3B-Thinking. Please consider using this updated model instead of the previous version.
Meet 10.7B Solar: Elevating Performance with Upstage Depth UP Scaling!
SmolLM is a series of small language models available in three sizes: 135M, 360M, and 1.7B parameters.
MiniCPM 技术报告 Technical Report OmniLMM 多模态模型 Multi-modal Model CPM-C 千亿模型试用 ~100B Model Trial
Building the Next Generation of Open-Source and Bilingual LLMs
SmolVLM is a compact open multimodal model that accepts arbitrary sequences of image and text inputs to produce text outputs. Designed for efficiency, SmolVLM can answer questions about images, describe visual content, create stories grounded on multiple images, or function as a…
Model Summary: Granite-3.1-2B-Instruct is a 2B parameter long-context instruct model finetuned from Granite-3.1-2B-Base using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets tailored for solving long context pr…