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Large Language ModelsAI Business & IndustryTHE DECODERPublished: Oct 7, 2026, 01:00 JST

Mistral Large 4 hits 38 points in Intelligence Index, a big leap

Mistral Large 4 hits 38 points in Intelligence Index, a big leap

3 Key Points

  1. What happened

    Mistral released a public preview of Mistral Large 4, a trillion-parameter model with 49 billion active parameters, available now via Mistral Studio's API; weights are expected at the end of October. It scores 38 points in Artificial Analysis's Intelligence Index, versus Claude Opus 5.5 (Max) at 58.

  2. Why it matters

    The 38-point result is a major jump from Mistral's previous models, which scored 9 and 14 points, and it edges past GLM-5.2; the company is pitching its security capabilities as a reason enterprises should choose it over more capable closed rivals.

  3. What to watch

    The model weights are expected at the end of October, and until then Mistral is red-teaming with security firms and government agencies; the company says the ongoing reinforcement-learning run shows no signs of plateauing and expects significant improvements over the coming weeks.

WHO IT HITSEnterprise security and IT teams that need to scan code or reproduce vulnerabilities may find closed US models unusable due to refusals, making Mistral's offering a potential alternative. The high refusal rates on malicious prompts also matter for compliance and risk officers evaluating whether to trust an open model with sensitive work.

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Context & Analysis

Mistral has been building its own infrastructure in Europe for months. In March, the company took out an $830 million loan for a data center near Paris, with 200 megawatts of compute capacity in Europe planned by the end of 2027. In May, Mistral renamed its chatbot Le Chat to Vibe and rebuilt it as a work tool, shifting focus from consumers toward enterprise customers. The current Series D round of 3 billion euros, the largest equity round ever raised by a European tech company, funds this compute expansion.

Mistral's emphasis on cybersecurity comes after CEO Arthur Mensch warned a French parliamentary commission in May that Europe risks becoming dependent on US models for cybersecurity. He said the French military's codebases shouldn't be scanned by Anthropic's Mythos, and that Mistral's own models could find the same vulnerabilities linked to Mythos. Mistral argues that closed models' safety filters block legitimate vulnerability research, while attackers jailbreak those same models anyway. How ML4 reliably distinguishes legitimate research from attack prep, Mistral doesn't explain.

The model's competitive position hinges on the ongoing reinforcement-learning run that Mistral says shows no signs of plateauing, with significant improvements expected over the coming weeks. If that bears out, ML4 could narrow the gap to Claude Opus 5.5 (Max)'s 58 points while strengthening its security pitch. But the weights are expected at the end of October, and until then ML4 remains proprietary and red-teamed with vetted partners.

FAQ
How does Mistral Large 4 perform compared to Mistral's previous models?
It scores 38 points in the Artificial Analysis Intelligence Index, a major step up from Mistral Large 3's 9 points and Mistral Medium 3.5's 14 points.
When will the model weights be available?
Mistral expects to release the weights, architecture details, and license at the end of October.
What is the pricing for using Mistral Large 4 through the API?
During the preview, Mistral charges $0.68 per million input tokens and $2.09 per million output tokens, with cached inputs at $0.07 per million. The documentation also lists prices at double those rates.

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