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CodestralvsMistral Large 2

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

Mistral Large 2 leads 3/5 categories

Head-to-Head Comparison

MetricCodestralMistral Large 2
Provider
Arena Rank
#8
Context Window
32K
128K
Input Pricing
$0.30/1M tokens
$2.00/1M tokens
Output Pricing
$0.90/1M tokens
$6.00/1M tokens
Parameters
22B
123B
Open Source
No
Yes
Best For
Code generation, code completion, debugging
Multilingual, coding, complex reasoning
Release Date
May 29, 2024
Jul 24, 2024

Codestral

Codestral, developed by Mistral AI, is a specialized code model with 22 billion parameters and a 32K token context window trained on over 80 programming languages. The model is optimized specifically for software development tasks including code completion, generation, refactoring, documentation, and test writing. Unlike general-purpose models, Codestral's focused training delivers stronger performance on code-specific tasks, particularly fill-in-the-middle completion for IDE integration. It features low-latency inference suitable for real-time autocomplete in development environments. Priced at $0.30 per million input tokens and $0.90 per million output tokens. Codestral powers coding assistants and integrates with popular development tools including VS Code and JetBrains IDEs. Its specialized architecture achieves competitive scores on HumanEval and MBPP benchmarks, rivaling much larger general-purpose models on coding tasks.

View Mistral AI profile →

Mistral Large 2

Mistral Large 2, developed by Mistral AI, is the company's most capable model with 123 billion parameters and a 128K token context window. The model excels at complex reasoning, coding, and multilingual tasks with particular strength across European languages. Mistral Large 2 supports function calling, JSON output, and system prompts for production deployments. As an open-source model, it can be deployed on enterprise infrastructure or accessed through Mistral's API, Azure, AWS, and Google Cloud. Priced at $2.00 per million input tokens and $6.00 per million output tokens through the API. It competes directly with GPT-4o and Claude Sonnet on quality benchmarks while offering deployment flexibility that proprietary models lack. Mistral Large 2 ranks #8 on the Chatbot Arena leaderboard, confirming its position as one of the strongest European-built AI models.

View Mistral AI profile →

Key Differences: Codestral vs Mistral Large 2

1

Codestral is 6.7x cheaper on average, making it the better choice for high-volume applications.

2

Mistral Large 2 supports a larger context window (128K), allowing it to process longer documents in a single request.

3

Mistral Large 2 is open-source (free to self-host and fine-tune) while Codestral is proprietary (API-only access).

4

Codestral has 22B parameters vs Mistral Large 2's 123B, which affects inference speed and capability.

C

When to use Codestral

  • +Budget is a concern and you need cost efficiency
  • +You prefer a managed API without infrastructure overhead
  • +Your use case involves code generation, code completion, debugging
View full Codestral specs →
M

When to use Mistral Large 2

  • +Quality matters more than cost
  • +You need to process long documents (128K context)
  • +You need to self-host or fine-tune the model
  • +Your use case involves multilingual, coding, complex reasoning
View full Mistral Large 2 specs →

Cost Analysis

At current pricing, Codestral is 6.7x more affordable than Mistral Large 2. For a typical enterprise workload processing 100M tokens per month:

Codestral monthly cost

$60

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

Mistral Large 2 monthly cost

$400

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

The Verdict

Mistral Large 2 wins our head-to-head comparison with 3 out of 5 category wins. It's the stronger choice for multilingual, coding, complex reasoning, though Codestral holds an edge in code generation, code completion, debugging. If cost is your primary concern, Codestral offers better value.

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

Frequently Asked Questions

Which is better, Codestral or Mistral Large 2?
In our head-to-head comparison, Mistral Large 2 leads in 3 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Mistral Large 2 excels at multilingual, coding, complex reasoning, while Codestral is better suited for code generation, code completion, debugging. The best choice depends on your specific requirements, budget, and use case.
How does Codestral pricing compare to Mistral Large 2?
Codestral charges $0.30 per 1M input tokens and $0.90 per 1M output tokens. Mistral Large 2 charges $2.00 per 1M input tokens and $6.00 per 1M output tokens. Codestral is the more affordable option, approximately 6.7x 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 Codestral and Mistral Large 2?
Codestral supports a 32K token context window, while Mistral Large 2 supports 128K tokens. Mistral Large 2 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 Codestral or Mistral Large 2 for free?
Codestral is a paid API model starting at $0.30 per 1M input tokens. Mistral Large 2 is a paid API model starting at $2.00 per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Codestral or Mistral Large 2?
Codestral's arena rank is not yet available, while Mistral Large 2 holds rank #8. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Codestral or Mistral Large 2 better for coding?
Codestral is specifically optimized for coding tasks. Mistral Large 2 is specifically optimized for coding tasks. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.