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CodestralvsMixtral 8x22B

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

Mixtral 8x22B leads 3/5 categories

Head-to-Head Comparison

MetricCodestralMixtral 8x22B
Provider
Arena Rank
#16
Context Window
32K
64K
Input Pricing
$0.30/1M tokens
$0.90/1M tokens
Output Pricing
$0.90/1M tokens
$2.70/1M tokens
Parameters
22B
176B (39B active)
Open Source
No
Yes
Best For
Code generation, code completion, debugging
Efficient reasoning, multilingual, coding
Release Date
May 29, 2024
Apr 17, 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 →

Mixtral 8x22B

Mixtral 8x22B, developed by Mistral AI, is a large Mixture-of-Experts model with 176 billion total parameters (39 billion active per token) and a 64K token context window. The model scales the MoE architecture to deliver stronger reasoning, coding, and multilingual performance while maintaining the efficiency advantages of sparse expert routing. It supports function calling and structured outputs for production agentic workflows. Free and open-source, Mixtral 8x22B can be deployed on enterprise GPU infrastructure for organizations requiring powerful, self-hosted AI. Priced at $0.90 per million input tokens through API providers. The model demonstrates competitive performance with proprietary models at significantly lower operational cost due to its efficient architecture. Mixtral 8x22B ranks #16 on the Chatbot Arena leaderboard, confirming strong capability for an open-weight MoE model.

View Mistral AI profile →

Key Differences: Codestral vs Mixtral 8x22B

1

Codestral is 3.0x cheaper on average, making it the better choice for high-volume applications.

2

Mixtral 8x22B supports a larger context window (64K), allowing it to process longer documents in a single request.

3

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

4

Codestral has 22B parameters vs Mixtral 8x22B's 176B (39B active), 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 Mixtral 8x22B

  • +Quality matters more than cost
  • +You need to process long documents (64K context)
  • +You need to self-host or fine-tune the model
  • +Your use case involves efficient reasoning, multilingual, coding
View full Mixtral 8x22B specs →

Cost Analysis

At current pricing, Codestral is 3.0x more affordable than Mixtral 8x22B. For a typical enterprise workload processing 100M tokens per month:

Codestral monthly cost

$60

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

Mixtral 8x22B monthly cost

$180

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

The Verdict

Mixtral 8x22B wins our head-to-head comparison with 3 out of 5 category wins. It's the stronger choice for efficient reasoning, multilingual, coding, 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 Mixtral 8x22B?
In our head-to-head comparison, Mixtral 8x22B leads in 3 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Mixtral 8x22B excels at efficient reasoning, multilingual, coding, 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 Mixtral 8x22B?
Codestral charges $0.30 per 1M input tokens and $0.90 per 1M output tokens. Mixtral 8x22B charges $0.90 per 1M input tokens and $2.70 per 1M output tokens. Codestral is the more affordable option, approximately 3.0x 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 Mixtral 8x22B?
Codestral supports a 32K token context window, while Mixtral 8x22B supports 64K tokens. Mixtral 8x22B 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 Mixtral 8x22B for free?
Codestral is a paid API model starting at $0.30 per 1M input tokens. Mixtral 8x22B is a paid API model starting at $0.90 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 Mixtral 8x22B?
Codestral's arena rank is not yet available, while Mixtral 8x22B holds rank #16. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Codestral or Mixtral 8x22B better for coding?
Codestral is specifically optimized for coding tasks. Mixtral 8x22B is specifically optimized for coding tasks. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.