👋 Hey, this is Ben with a 🔒 subscriber-only issue 🔒 of Ben’s Bites Pro. A weekly newsletter covering AI trends, ideas, business breakdowns and how companies use AI internally.
Subscribe now 18Today I’m diving deep into Mistral AI, who are making headlines after recently closing their (huge) Series A round. Launched just 7 months ago, they’re disrupting the LLM market. I want to look at how they’re doing it - and how you can take advantage.
This post covers:
What is Mistral?
Who’s behind it?
The timeline: What’s happened to date
Fundraising
Product Overview
A peek inside their seed deck 👀
Roadmap analysis. Are they achieving what they set out to do?
5 big reasons Mistral’s making waves 🌊
How people actually use Mistral
Opportunities and how you can take advantage
What developers think of Mistral
A French startup that develops fast, open-source and secure language models. Founded in 2023 by Arthur Mensch, Guillaume Lample, and Timothée Lacroix.
They’ve raised over $650M in funding, are valued at $2Bn, are less than a year old and have 22 employees.

monthly search volume for ‘mistral ai’
The company is important for a few reasons;
It’s actually open-source, you know like OpenAI was supposed to be? Or how LlaMA by Meta kinda is but isn’t?
It’s developed 2 AI models in less than a year.
It’s French.
The founders are 3 researchers from DeepMind and Meta who aimed to beat GPT 3.5 by year-end. And they did.

They started a new company, Mistral AI, in May 2023 and had the biggest seed round in the EU within 4 weeks.
Mistral’s CEO Arthur Mensch was at Deepmind for a little less than 3 years where he worked on research around the retrieval-based models, sparse mixture of experts and then co-authored the famous Chinchilla paper on the scaling laws of LLMs.
So he’s legit.
CTO Timothée Lacroix and Chief Scientist Guillaume Lample were at Meta. They both have nearly a decade of experience in research. And, they had just been part of the team behind Meta’s own LLM, LLaMA in February.
Also legit.
Here’s a quick rundown of what’s happened since then:
June 13 2023 - Seed Funding78 of $113M.
Sept 27 2023 - Their first model Mistral 7B251 released (via a torrent link on Twitter X).
Dec 8 2023 - Mixtral 8x7B MoE released—their second model, again released via a torrent link96.
Dec 11 2023 - Launch of its API and developer platform. Followed by the news of its Series A ($415M)59 plus debt financing ($130M) by NVIDIA and Salesforce.
Let’s take a quick look at those rounds because they are eyewatering…
The first funding round took place on 13th June 2023. The company raised $113 million, led by Lightspeed Venture Partners.
Other participants included Redpoint, Index Ventures, Xavier Niel, JCDecaux Holding, Rodolphe Saadé, Motier Ventures, La Famiglia, Headline, Exor Ventures, Sofina, First Minute Capital, and LocalGlobe. Notably, French investment bank Bpifrance and former Google CEO Eric Schmidt were also shareholders.
This funding round valued Mistral AI at $260 million.
The Series A round was announced on 11th December 2023. In this round, Mistral AI raised $415 million, led by Andreessen Horowitz.
Other participants included Lightspeed Venture Partners, Salesforce, BNP Paribas, General Catalyst, Elad Gil, Conviction, and others. Crunchbase also differentiates Nvidia and Salesforce as debt investors with an additional $130M.
This funding round valued the company at approximately $2 billion.
A 7B dense transformer, fast-deployed and easily customisable. Small, yet powerful for a variety of use cases. Supports English and code, and an 8k context window.
A 7B sparse Mixture-of-Experts model with stronger capabilities than Mistral 7B. Uses 12B active parameters out of 45B total. Supports multiple languages, code and 32k context window.
It comes in 3 versions:
tiny
small
medium
State-of-the-art semantic embeddings from text chunks. Powers your RAG application.
Efficient chat-based API for text generation, using our open and optimised models under the hood.
You can play with it on; Together’s Playground212, Perplexity773, Vercel107, Langchain’s Langsmith709 and Hugging Face246.
To use the official API check out their docs969, plus available on Together80, Anyscale99, Replicate75, Perplexity561 and many others.
Their seed deck has been floating around the internet. Which you can view here1,165.
And there are a few things to mention specifically.
They believe the most value is in the hard-to-make tech e.g. the models themselves. Trained on powerful machines, trillions of words, high-quality sources—which is one barrier to entry.
The other barrier? A talented (and capable) team.
There were a few others on the team at the time of the first raise:
Jean-Charles Samuelian60 - CEO of Alan438 (looks like he is a Co-Founding advisor & Board Member at Mistral)
Charles Gorintin45 - CTO of Alan438 (also Co-Founding Advisor at Mistral)
Cédric O214 - Former French Secretary of State for Digital Affairs (also Co-Founding Advisor at Mistral)
Continuing through their deck…
The Mistral team wanted to cement itself as the European leader.
Closed-source vs open-source. The big debate.
Mistral believes (as do many others, myself included) that there are several concerns with closed AI approaches; businesses have to send sensitive data to it, only exposing the outputs doesn’t help connect with other components (retrieval, structure inputs etc) and the data used to train the models are secret (so we assume it can do some things it perhaps hasn’t been trained on).
Now the bold stuff.
How?
They’ll take a more open approach to model development.
Tighter integration with customers’ workflows.
Increase focus on data sources and control.
Propose unmatched guarantees on security and privacy.
There’s a lot more detail in their deck1,165 on the above 4 points.
As far as business focus goes…
Let’s look at their roadmap (remember this was from pre-June) and see what they planned on doing compared to what has happened.
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How Mistral AI, an OpenAI competitor, rocketed to $2Bn in <12 months
61 readers clicked at least once. 22 links, 22 with clicks. Heat is relative to the most clicked link in this issue.
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