Model Comparison

Codestral-22B vs Llama 3.1 Nemotron Ultra 253B v1Which is better in 2026?

Comparing Codestral-22B and Llama 3.1 Nemotron Ultra 253B v1 across benchmarks, pricing, and capabilities.

Verdict: Codestral-22B vs Llama 3.1 Nemotron Ultra 253B v1 — which is better?

Codestral-22B (by Mistral AI) and Llama 3.1 Nemotron Ultra 253B v1 (by NVIDIA) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose Codestral-22B if…

  • you are already invested in the Mistral AI ecosystem

Choose Llama 3.1 Nemotron Ultra 253B v1 if…

  • you want the most recent training data — it shipped Apr 2025

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and Llama 3.1 Nemotron Ultra 253B v1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

230.8B diff

Llama 3.1 Nemotron Ultra 253B v1 has 230.8B more parameters than Codestral-22B, making it 1039.6% larger.

Mistral AI
Codestral-22B
22.2Bparameters
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1
253.0Bparameters
22.2B
Codestral-22B
253.0B
Llama 3.1 Nemotron Ultra 253B v1

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Llama 3.1 Nemotron Ultra 253B v1 uses Llama 3.1 Community License.

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

Codestral-22B

MNPL-0.1

Open weights

Llama 3.1 Nemotron Ultra 253B v1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Llama 3.1 Nemotron Ultra 253B v1 was released on 2025-04-07.

Llama 3.1 Nemotron Ultra 253B v1 is 10 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.1 years ago

Llama 3.1 Nemotron Ultra 253B v1

Apr 7, 2025

1.2 years ago

10mo newer

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron Ultra 253B v1 has a documented knowledge cutoff of 2023-12-01, while Codestral-22B's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron Ultra 253B v1's training data extends to 2023-12-01, but cannot make a direct comparison without Codestral-22B's cutoff date.

Codestral-22B

—

Llama 3.1 Nemotron Ultra 253B v1

Dec 2023

Outputs Comparison

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Key Takeaways

Mistral AI

No standout differentiators in the data we have for this pair.

NVIDIA

No standout differentiators in the data we have for this pair.

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Codestral-22B and Llama 3.1 Nemotron Ultra 253B v1 side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Llama 3.1 Nemotron Ultra 253B v1
Open in Playground
AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1

FAQ

Common questions about Codestral-22B vs Llama 3.1 Nemotron Ultra 253B v1.

Which is better, Codestral-22B or Llama 3.1 Nemotron Ultra 253B v1?

Codestral-22B (Mistral AI) and Llama 3.1 Nemotron Ultra 253B v1 (NVIDIA) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Codestral-22B compare to Llama 3.1 Nemotron Ultra 253B v1 in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Llama 3.1 Nemotron Ultra 253B v1 scores MATH-500: 97.0%, IFEval: 89.5%, GPQA: 76.0%, BFCL v2: 74.1%, AIME 2025: 72.5%.

What are the main differences between Codestral-22B and Llama 3.1 Nemotron Ultra 253B v1?

Key differences include licensing (MNPL-0.1 vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and Llama 3.1 Nemotron Ultra 253B v1?

Codestral-22B is developed by Mistral AI and Llama 3.1 Nemotron Ultra 253B v1 is developed by NVIDIA.

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