What is Mixtral 8x7B?

Mixtral 8x7B is a legacy AI model, developed by Mistral and released in 2023-12. It handles general AI tasks including writing, analysis, summarisation, and question answering.

Is Mixtral 8x7B open-source or open-weight?

Mixtral 8x7B is an open-weight model. Its trained weights are publicly available for download, self-hosting, and fine-tuning. You can run it on your own infrastructure without per-token API fees. Note that open-weight is not the same as open-source: the training code and data may not be fully public.

What is Mixtral 8x7B's context window?

Mixtral 8x7B supports a 32K-token context window, adequate for most documents and multi-turn applications.

What benchmarks has Mixtral 8x7B been evaluated on?

Mixtral 8x7B has been evaluated on: HumanEval pass@1 (80.5%). Scores tagged SR are self-reported by the provider; scores tagged 3P or AA have been independently verified by third parties.

Is Mixtral 8x7B available in FlowHunt?

Yes — Mixtral 8x7B is directly available in FlowHunt. You can use it to build AI agents, automated workflows, chatbots, and document processing pipelines without any additional setup.

How does Mixtral 8x7B compare to other AI models?

You can compare Mixtral 8x7B against all 24 models tracked on the FlowHunt AI Leaderboard using the sortable benchmark table. The Benchmark Rankings section on this page shows Mixtral 8x7B's position on each benchmark it has been evaluated on.

Mistral

Mixtral 8x7B

LegacyOpen-weightAvailable in FlowHunt

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Mixtral 8x7B is a legacy AI model, developed by Mistral and released in December 2023. As an open-weight model, its trained weights are publicly available — you can self-host it, fine-tune it on proprietary data, or run it on-premise without API dependencies. Its 32K-token context window is shorter than current frontier models, which may limit performance on long documents.

On the FlowHunt AI Leaderboard it is one of 24 tracked models, evaluated across 1 benchmark. Standout scores: 80.5% on HumanEval (#2 of 2).

Mixtral 8x7B was released on December 1, 2023 without prior announcement — Mistral dropped a torrent magnet link on Twitter and let the community discover what it had built. The release introduced mixture-of-experts architecture to the open-weight AI mainstream: 8 expert networks of 7B parameters each, with 2 experts activated per token, yielding 12.9B active and 46.7B total parameters. At launch it matched GPT-3.5 on most benchmarks while being fully open-weight and runnable on consumer GPUs. Mixtral 8x7B effectively established the MoE playbook that DeepSeek, Qwen, NVIDIA, Meta, and other labs have since adopted for their own open-weight architectures. By 2026 it sits in the Legacy tier — substantially outpaced on every benchmark — but its historical significance in democratising MoE-class performance is considerable.

Note: Pioneered sparse MoE. GPT-3.5 class. Far below 2026 frontier.

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Released: December 2023
Parameters: 12.9B/46.7B MoE
Context: 32K tokens
Weights: Open
Tier: Legacy
Provider: Mistral

Mixtral 8x7B Benchmark Rankings

Rank among all 24 models tracked on this leaderboard. SR = self-reported · 3P / AA / C = independently verified.

Benchmark	Score	Rank	Source	What it measures
HumanEval pass@1	80.5%	2 of 2	SR	Python code generation (saturated at frontier)

Detailed Benchmark Scores

HumEval SR

80.5%

Python code generation (saturated at frontier)

About Mistral

Mistral Founded 2023 · Paris, France

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Mistral AI is a French AI company founded in April 2023 by Arthur Mensch (formerly of Google DeepMind), Guillaume Lample, and Timothée Lacroix (both formerly of Meta AI Research). The company positions itself as a European champion in generative AI, combining a commercial API business with strategic open-weight releases. Mistral's flagship Large series and Apache 2.0-licensed models have made it the most prominent non-US, non-Chinese provider on most AI leaderboards. The company maintains EU headquarters in Paris, emphasises GDPR and EU regulatory compliance, and has articulated a distinct regulatory philosophy calling for lighter regulation of open-weight models compared to closed API systems.

Use Cases

What to Use Mixtral 8x7B For

Self-Hosted & Private Deployments: Mixtral 8x7B is open-weight (12.9B/46.7B MoE parameters) — its trained weights are publicly available for download and self-deployment. Run it on your own GPU hardware or private cloud to ensure data never leaves your environment, eliminate per-token API costs at scale, or fine-tune the model on proprietary datasets.

Strengths & Limitations

Strengths

Self-hosted & data-private deployments (open-weight)

Limitations

Significantly behind 2026 frontier models on agentic coding and complex reasoning
Short context window (32K) — limited for long documents

More to Compare

Related AI Models

Browse the Full AI Model Leaderboard

Compare all 24 models across 11 benchmarks — sortable, sourced, and updated June 2026.

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Frequently asked questions

: Mixtral 8x7B is a legacy AI model, developed by Mistral and released in 2023-12. It handles general AI tasks including writing, analysis, summarisation, and question answering.
: Mixtral 8x7B is an open-weight model. Its trained weights are publicly available for download, self-hosting, and fine-tuning. You can run it on your own infrastructure without per-token API fees. Note that open-weight is not the same as open-source: the training code and data may not be fully public.
: Mixtral 8x7B supports a 32K-token context window, adequate for most documents and multi-turn applications.
: Mixtral 8x7B has been evaluated on: HumanEval pass@1 (80.5%). Scores tagged SR are self-reported by the provider; scores tagged 3P or AA have been independently verified by third parties.
: Yes — Mixtral 8x7B is directly available in FlowHunt. You can use it to build AI agents, automated workflows, chatbots, and document processing pipelines without any additional setup.
: You can compare Mixtral 8x7B against all 24 models tracked on the FlowHunt AI Leaderboard using the sortable benchmark table. The Benchmark Rankings section on this page shows Mixtral 8x7B's position on each benchmark it has been evaluated on.

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