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Codestral-22B vs Muse Spark Open

Muse Spark Open leads the LLM Stats Score 44.9 to -0.3.

Mistral AI · Meta · Updated for 2026

Which is better?

Muse Spark Open leads the overall LLM Stats Score 44.9 to -0.3, ranking #43 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Codestral-22B

  • you are already invested in the Mistral AI ecosystem

Choose Muse Spark Open

  • overall performance matters — it scores 44.9 and ranks #43 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
Muse Spark Open
Meta
Core performance indexes
LLM Stats Score
-0.3
#350
44.9
#43
Reasoning
-0.4
#343
45.2
#39
Coding
2.4
#248
33.0
#42
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$1.25 / M
Output price
— / M
$4.25 / M
Context window
—
1,048,576

Individual benchmarks

7 reported for Codestral-22B · 17 for Muse Spark Open

No common benchmarks found

Codestral-22B and Muse Spark Opendon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

793.8B diff

Muse Spark Open has 793.8B more parameters than Codestral-22B, making it 3575.7% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Meta
Muse Spark Open
816.0Bparameters
22.2B
Codestral-22B
816.0B
Muse Spark Open

Context Window

Maximum input and output token capacity

Only Muse Spark Open specifies input context (1,048,576 tokens). Only Muse Spark Open specifies output context (1,048,576 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Meta
Muse Spark Open
Input1,048,576 tokens
Output1,048,576 tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Muse Spark Open supports multimodal inputs, whereas Codestral-22B does not.

Muse Spark Open can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Muse Spark Open

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Muse Spark Open uses Muse Model License.

License differences may affect how you can use these models in commercial or open-source projects.

Codestral-22B

MNPL-0.1

Open weights

Muse Spark Open

Muse Model License

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Muse Spark Open was released on 2026-10-15.

Muse Spark Open is 29 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.4 years ago

Muse Spark Open

Oct 15, 2026

5 days ago

2.4yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Codestral-22B and Muse Spark Open side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Muse Spark Open
Open in Playground

FAQ

Common questions about Codestral-22B vs Muse Spark Open.

Which is better, Codestral-22B or Muse Spark Open?

Muse Spark Open leads the LLM Stats Score 44.9 to -0.3. Codestral-22B is made by Mistral AI and Muse Spark Open is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Codestral-22B compare to Muse Spark Open in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Muse Spark Open scores MCP Atlas: 89.2%, GPQA: 89.0%, OSWorld-Verified: 80.4%, BabyVision: 80.2%, Terminal-Bench 2.1: 76.4%.

What are the context window sizes for Codestral-22B and Muse Spark Open?

Codestral-22B supports an unknown number of tokens and Muse Spark Open supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Codestral-22B and Muse Spark Open?

Key differences include LLM Stats Score (-0.3 vs 44.9), multimodal support (no vs yes), licensing (MNPL-0.1 vs Muse Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and Muse Spark Open?

Codestral-22B is developed by Mistral AI and Muse Spark Open is developed by Meta.

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