Mistral AI raises $415 million and launches API service


Paris-based AI startup Mistral AI has raised 385 million euros (about $415) in a funding round led by Silicon Valley venture capital firm Andreessen Horowitz and early investor Lightspeed Ventures.

The seven-month-old company, founded by former Deepmind researchers from Alphabet Inc. and Meta Platforms Inc. and currently employing 22 people, is valued at about $2 billion. It is also releasing a new open-source model and providing access to its API platform.

Open-source software for chatbots and generative AI tools

Mistral AI develops open-source models to power chatbots and other generative AI tools. Similar to Meta with Llama, Mistral’s business plan is to first achieve market penetration with its open-source models and then offer premium services around these models or charge for high-quality models.

Other investors in this round include Salesforce Inc, BNP Paribas, CMA CGM, General Catalyst, Elad Gil, Emerson Collective, Conviction, Bpifrance, La Famiglia, Eric Schmidt, New Wave, Motier Ventures and Sofina.



In September, Mistral released its first small-large language model, the capable Mistral 7B, which quickly caught on in the open-source community. With Mixtral MoE, Mistral has now released a mixture-of-experts model that follows the suspected GPT-4 architecture.

Image: Mistral AI

It networks eight 7B models and is said to outperform GPT-3.5 and Llama 2 with 70B in benchmarks. The model supports French, Italian, German, and Spanish in addition to English and offers a 32k context window.

Mistral launches API access

Mistral AI has also launched beta access to its first platform services, including three text chat endpoints and an embedding endpoint. The endpoints, named mistral-tiny, mistral-small (Mixtral MoE) and mistral-medium, offer access to different AI models, with the medium endpoint using a more capable prototype model that scores around 75 percent in the MMLU, significantly outperforming GPT-3.5 in this benchmark.

Image: Mistral AI

The platform offers customization techniques such as fine-tuning and direct preference optimization for easy-to-control models. Mistral-tiny works in English, while mistral-small and mistral-medium support multiple languages and codes.

The platform also includes an embedding model, mistral-embed, designed for retrieval purposes. The APIs comply with the common specifications for chat interfaces, or as Mistral puts it: “Our APIs follow the specifications of the popular chat interface initially proposed by our dearest competitor.”


Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top