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Mixtral 8x22BvsMistral Large

Mistral AI vs Mistral AI — Side-by-side model comparison

Mistral Large leads 5/5 categories

Head-to-Head Comparison

MetricMixtral 8x22BMistral Large
Provider
Arena Rank
#16
#8
Context Window
64K
256K
Input Pricing
$0.90/1M tokens
$0.50/1M tokens
Output Pricing
$2.70/1M tokens
$1.50/1M tokens
Parameters
176B (39B active)
675B MoE (41B active)
Open Source
Yes
No
Best For
Efficient reasoning, multilingual, coding
European privacy, multilingual, code
Release Date
Apr 17, 2024

Mixtral 8x22B

Mixtral 8x22B is Mistral AI's large mixture-of-experts model that uses a sparse architecture to achieve strong performance while activating only a fraction of its total parameters per token. With 176 billion total parameters but only 39 billion active per forward pass, it delivers efficiency that makes it practical to deploy despite its size. It features a 64K context window and excels at multilingual tasks, coding, and mathematical reasoning.

View Mistral AI profile →

Mistral Large

Mistral Large is the flagship model from Mistral AI, Europe's leading AI company. Built in Paris with a focus on multilingual capability and European language support, it delivers strong performance on coding, reasoning, and enterprise tasks while offering competitive pricing. The model features a 256K context window and supports function calling, JSON output, and system prompts. Mistral Large is particularly strong at code generation, technical writing, and structured data extraction. As a European-developed model, it appeals to organizations prioritizing data sovereignty and EU compliance. Mistral AI has positioned this model as the enterprise alternative to American-built models, with deployment options through their own API, Azure, AWS, and Google Cloud. The company has rapidly grown to become one of the most valuable AI startups globally.

View Mistral AI profile →

Key Differences: Mixtral 8x22B vs Mistral Large

1

Mistral Large ranks higher in arena benchmarks (#8) indicating stronger overall performance.

2

Mistral Large is 1.8x cheaper on average, making it the better choice for high-volume applications.

3

Mistral Large supports a larger context window (256K), allowing it to process longer documents in a single request.

4

Mixtral 8x22B is open-source (free to self-host and fine-tune) while Mistral Large is proprietary (API-only access).

5

Mixtral 8x22B has 176B (39B active) parameters vs Mistral Large's 675B MoE (41B active), which affects inference speed and capability.

M

When to use Mixtral 8x22B

  • +Quality matters more than cost
  • +You need to self-host or fine-tune the model
  • +Your use case involves efficient reasoning, multilingual, coding
View full Mixtral 8x22B specs →
M

When to use Mistral Large

  • +You need the highest quality output based on arena rankings
  • +Budget is a concern and you need cost efficiency
  • +You need to process long documents (256K context)
  • +You prefer a managed API without infrastructure overhead
  • +Your use case involves european privacy, multilingual, code
View full Mistral Large specs →

Cost Analysis

At current pricing, Mistral Large is 1.8x more affordable than Mixtral 8x22B. For a typical enterprise workload processing 100M tokens per month:

Mixtral 8x22B monthly cost

$180

100M tokens/mo (50/50 in/out)

Mistral Large monthly cost

$100

100M tokens/mo (50/50 in/out)

The Verdict

Mistral Large wins our head-to-head comparison with 5 out of 5 category wins. It's the stronger choice for european privacy, multilingual, code, though Mixtral 8x22B holds an edge in efficient reasoning, multilingual, coding.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Mixtral 8x22B or Mistral Large?
In our head-to-head comparison, Mistral Large leads in 5 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Mistral Large excels at european privacy, multilingual, code, while Mixtral 8x22B is better suited for efficient reasoning, multilingual, coding. The best choice depends on your specific requirements, budget, and use case.
How does Mixtral 8x22B pricing compare to Mistral Large?
Mixtral 8x22B charges $0.90 per 1M input tokens and $2.70 per 1M output tokens. Mistral Large charges $0.50 per 1M input tokens and $1.50 per 1M output tokens. Mistral Large is the more affordable option, approximately 1.8x cheaper on average. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Mixtral 8x22B and Mistral Large?
Mixtral 8x22B supports a 64K token context window, while Mistral Large supports 256K tokens. Mistral Large can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Mixtral 8x22B or Mistral Large for free?
Mixtral 8x22B is a paid API model starting at $0.90 per 1M input tokens. Mistral Large is a paid API model starting at $0.50 per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Mixtral 8x22B or Mistral Large?
Mixtral 8x22B holds arena rank #16, while Mistral Large holds rank #8. Mistral Large performs better in overall arena benchmarks, which aggregate human preference ratings across coding, reasoning, and general tasks. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Mixtral 8x22B or Mistral Large better for coding?
Mixtral 8x22B is specifically optimized for coding tasks. Mistral Large is specifically optimized for coding tasks. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.