The 7B model released by Mistral AI, updated to version 0.3.
OLMo 2 is a new family of 7B and 13B models trained on up to 5T tokens. These models are on par with or better than equivalently sized fully open models, and competitive with open-weight models such as Llama 3.1 on English academic benchmarks.
Llama 2 is a collection of foundation language models ranging from 7B to 70B parameters.
StarCoder2 is the next generation of transparently trained open code LLMs that comes in three sizes: 3B, 7B and 15B parameters.
OpenHermes 2.5 is a 7B model fine-tuned by Teknium on Mistral with fully open datasets.
InternLM2.5 is a 7B parameter model tailored for practical scenarios with outstanding reasoning capability.
Mistral OpenOrca is a 7 billion parameter model, fine-tuned on top of the Mistral 7B model using the OpenOrca dataset.
A 7B and 15B uncensored variant of the Dolphin model family that excels at coding, based on StarCoder2.
Stable Code 3B is a coding model with instruct and code completion variants on par with models such as Code Llama 7B that are 2.5x larger.
Wizard Vicuna Uncensored is a 7B, 13B, and 30B parameter model based on Llama 2 uncensored by Eric Hartford.
BakLLaVA is a multimodal model consisting of the Mistral 7B base model augmented with the LLaVA architecture.
MathΣtral: a 7B model designed for math reasoning and scientific discovery by Mistral AI.
7B parameter text-to-SQL model made by MotherDuck and Numbers Station.
A 7B chat model fine-tuned with high-quality data and based on Zephyr.
🎩 Magicoder is a family of 7B parameter models trained on 75K synthetic instruction data using OSS-Instruct, a novel approach to enlightening LLMs with open-source code snippets.
Our most capable model to date, designed for long-horizon work. 70.2% on Terminal-Bench 2.1 at 118B-A8B.
Llama 3.1 is a new state-of-the-art model from Meta available in 8B, 70B and 405B parameter sizes.
New state of the art 70B model. Llama 3.3 70B offers similar performance compared to the Llama 3.1 405B model.
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.