The AI arena is free today

Open Superagent

Codestral-22B vs GPT-6 Luna

GPT-6 Luna leads the LLM Stats Score 44.5 to 0.0.

Mistral AI · OpenAI · Updated for 2026

Which is better?

GPT-6 Luna leads the overall LLM Stats Score 44.5 to 0.0, ranking #40 overall.

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

Choose Codestral-22B

  • you need open weights you can self-host or fine-tune

Choose GPT-6 Luna

  • overall performance matters — it scores 44.5 and ranks #40 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
GPT-6 Luna
OpenAI
Core performance indexes
LLM Stats Score
0.0
#332
44.5
#40
Reasoning
-0.1
#324
40.0
#58
Coding
2.5
#231
31.4
#47
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.10 / M
Output price
— / M
$0.50 / M
Context window
—
1,050,000

Individual benchmarks

7 reported for Codestral-22B · 5 for GPT-6 Luna

No common benchmarks found

Codestral-22B and GPT-6 Lunadon'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

Context Window

Maximum input and output token capacity

Only GPT-6 Luna specifies input context (1,050,000 tokens). Only GPT-6 Luna specifies output context (128,000 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
OpenAI
GPT-6 Luna
Input1,050,000 tokens
Output128,000 tokens
Wed Sep 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-6 Luna supports multimodal inputs, whereas Codestral-22B does not.

GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

GPT-6 Luna

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while GPT-6 Luna uses a proprietary license.

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

Codestral-22B

MNPL-0.1

Open weights

GPT-6 Luna

Proprietary

Closed source

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while GPT-6 Luna was released on 2026-09-22.

GPT-6 Luna is 28 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.3 years ago

GPT-6 Luna

Sep 22, 2026

0 days ago

2.3yr newer

Knowledge Cutoff

When training data ends

GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while Codestral-22B's cutoff date is not specified.

We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without Codestral-22B's cutoff date.

Codestral-22B

—

GPT-6 Luna

May 2026

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Codestral-22B and GPT-6 Luna side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
GPT-6 Luna
Open in Playground

FAQ

Common questions about Codestral-22B vs GPT-6 Luna.

Which is better, Codestral-22B or GPT-6 Luna?

GPT-6 Luna leads the LLM Stats Score 44.5 to 0.0. Codestral-22B is made by Mistral AI and GPT-6 Luna is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Codestral-22B compare to GPT-6 Luna in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. GPT-6 Luna scores DeepSWE 1.1: 66.6%, OSWorld 2.0: 52.7%, Agents' Last Exam: 50.9%, FrontierCode 1.1: 42.4%, AutomationBench v1.0.6: 20.7%.

What are the context window sizes for Codestral-22B and GPT-6 Luna?

Codestral-22B supports an unknown number of tokens and GPT-6 Luna supports 1.1M 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 GPT-6 Luna?

Key differences include LLM Stats Score (0.0 vs 44.5), multimodal support (no vs yes), licensing (MNPL-0.1 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and GPT-6 Luna?

Codestral-22B is developed by Mistral AI and GPT-6 Luna is developed by OpenAI.

Related comparisons