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Mistral LargevsMistral Small

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

Mistral Large leads 3/5 categories

Head-to-Head Comparison

MetricMistral LargeMistral Small
Provider
Arena Rank
#8
#19
Context Window
256K
32K
Input Pricing
$0.50/1M tokens
$0.20/1M tokens
Output Pricing
$1.50/1M tokens
$0.60/1M tokens
Parameters
675B MoE (41B active)
22B
Open Source
No
Yes
Best For
European privacy, multilingual, code
Fast inference, cost-effective tasks, chat
Release Date
Sep 18, 2024

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 →

Mistral Small

Mistral Small, developed by Mistral AI, is a compact 22 billion parameter model with a 32K token context window optimized for fast inference and low deployment costs. The model handles coding, summarization, classification, and conversational tasks while maintaining the quality standards established by the Mistral model family. Its small footprint makes it suitable for edge deployment, cost-sensitive production applications, and use cases requiring low-latency responses. Priced at $0.20 per million input tokens and $0.60 per million output tokens, it offers affordable access to Mistral's technology. As an open-source model, it can also be self-hosted without API costs. Mistral Small ranks #19 on the Chatbot Arena leaderboard, demonstrating competitive performance for its compact size and establishing it as a strong option for budget-conscious deployments.

View Mistral AI profile →

Key Differences: Mistral Large vs Mistral Small

1

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

2

Mistral Small is 2.5x 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

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

5

Mistral Large has 675B MoE (41B active) parameters vs Mistral Small's 22B, which affects inference speed and capability.

M

When to use Mistral Large

  • +You need the highest quality output based on arena rankings
  • +Quality matters more than cost
  • +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 →
M

When to use Mistral Small

  • +Budget is a concern and you need cost efficiency
  • +You need to self-host or fine-tune the model
  • +Your use case involves fast inference, cost-effective tasks, chat
View full Mistral Small specs →

Cost Analysis

At current pricing, Mistral Small is 2.5x more affordable than Mistral Large. For a typical enterprise workload processing 100M tokens per month:

Mistral Large monthly cost

$100

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

Mistral Small monthly cost

$40

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

The Verdict

Mistral Large wins our head-to-head comparison with 3 out of 5 category wins. It's the stronger choice for european privacy, multilingual, code, though Mistral Small holds an edge in fast inference, cost-effective tasks, chat. If cost is your primary concern, Mistral Small offers better value.

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

Frequently Asked Questions

Which is better, Mistral Large or Mistral Small?
In our head-to-head comparison, Mistral Large leads in 3 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Mistral Large excels at european privacy, multilingual, code, while Mistral Small is better suited for fast inference, cost-effective tasks, chat. The best choice depends on your specific requirements, budget, and use case.
How does Mistral Large pricing compare to Mistral Small?
Mistral Large charges $0.50 per 1M input tokens and $1.50 per 1M output tokens. Mistral Small charges $0.20 per 1M input tokens and $0.60 per 1M output tokens. Mistral Small is the more affordable option, approximately 2.5x 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 Mistral Large and Mistral Small?
Mistral Large supports a 256K token context window, while Mistral Small supports 32K 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 Mistral Large or Mistral Small for free?
Mistral Large is a paid API model starting at $0.50 per 1M input tokens. Mistral Small is a paid API model starting at $0.20 per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Mistral Large or Mistral Small?
Mistral Large holds arena rank #8, while Mistral Small holds rank #19. 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 Mistral Large or Mistral Small better for coding?
Mistral Large is specifically optimized for coding tasks. Mistral Small's primary strength is fast inference, cost-effective tasks, chat. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.