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Llama vs Mistral

The two titans of open source AI go head-to-head. Compare 8 Meta Llama models against 18 Mistral AI models on scores, pricing, context windows, and capabilities. Data updated hourly.

Provider Overview

Side-by-side snapshot of Meta and Mistral AI as open source LLM providers.

Meta (Llama)Open Source

Models

8

Free Models

0

Max Context

1.3M

Avg Output $/1M

$0.326

VisionFunction CallingJSON Mode
Mistral AIOpen Source

Models

18

Free Models

0

Max Context

262K

Avg Output $/1M

$1.93

VisionReasoningFunction CallingJSON Mode

All Models Ranked by Score

26 models from Meta and Mistral AI sorted by composite score. Click any model for full details.

Key Head-to-Head Matchups

Top models from each provider paired by rank. Click to see the full comparison.

Llama 4 Maverick

Meta

681.0M$0.800
4/7 capabilities
Mistral Medium 3.5

Mistral AI

$7.50262K72
5/7 capabilities
Llama 3.3 70B Instruct

Meta

67131K$0.320
3/7 capabilities
Mistral Large 3 2512

Mistral AI

$1.50262K67
4/7 capabilities
Llama 3.1 70B Instruct

Meta

65131K$0.400
3/7 capabilities
Mistral Large 2407

Mistral AI

$6.00131K66
3/7 capabilities

Capability Coverage Comparison

Which capabilities each provider supports across their model lineup.

CapabilityMetaMistral AI
Vision3 models10 models
Function Calling5 models16 models
Streaming8 models18 models
JSON Mode7 models17 models
Reasoning--2 models
Web Search----
Image Output----

The Open Source LLM Showdown

Meta and Mistral AI represent two distinct approaches to open source AI. Here is what sets each apart and why this rivalry drives innovation for everyone.

Both Are Truly Open Source

Meta and Mistral AI both release models with open weights, enabling self-hosting, fine-tuning, and community-driven improvements. Both have become pillars of the open source AI ecosystem.

Different Design Philosophies

Meta's Llama family focuses on scale and broad capability, with models ranging from compact to frontier-class. Mistral AI emphasizes efficiency and performance per parameter, often punching above their weight class.

Pricing & Accessibility

Both providers offer free and paid tiers via API. Mistral tends to offer competitively priced smaller models, while Meta's Llama ecosystem benefits from wide third-party hosting and fine-tuning support.

Enterprise & Self-Hosting

Both model families can be self-hosted on your own infrastructure. Llama has broader community tooling, while Mistral offers commercial licenses and enterprise-focused deployment options.

Who Wins?

There is no single winner in the Llama vs Mistral debate. Meta excels when you need large-scale models backed by massive research investment, while Mistral AI shines with efficient, well-tuned models that deliver strong results at competitive price points. The real winners are developers who benefit from two major players pushing open source AI forward. Your best choice depends on your specific use case, deployment constraints, and budget.

Currently, Meta's top model Llama 4 Maverick scores 68, while Mistral AI's top model Mistral Medium 3.5 scores 72.

Explore More Comparisons

Dive deeper into open source model rankings, head-to-head comparisons, and the full AI leaderboard.

Frequently Asked Questions

Llama 3.3 70B generally outperforms Mistral Large on benchmarks. However, Mistral’s Mixtral architecture offers excellent efficiency, and Codestral is strong for coding. Both are excellent open-source options.

Both are great for self-hosting. Llama has broader community support and more fine-tuned variants. Mistral’s Mixtral uses mixture-of-experts for better efficiency, meaning comparable quality with lower hardware requirements.

Both offer open-weight models free to download and use. Llama has a permissive license allowing commercial use. Mistral offers some models under Apache 2.0 and others under a commercial license — check each model’s specific terms.

Llama vs Mistral - Best Open Source LLM? (2026) | LM Market Cap