Model Comparison

Codestral-22B vs Jamba 1.5 Mini

Comparing Codestral-22B and Jamba 1.5 Mini across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and Jamba 1.5 Mini don'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

29.8B diff

Jamba 1.5 Mini has 29.8B more parameters than Codestral-22B, making it 134.2% larger.

Mistral AI
Codestral-22B
22.2Bparameters
AI21 Labs
Jamba 1.5 Mini
52.0Bparameters
22.2B
Codestral-22B
52.0B
Jamba 1.5 Mini

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Mini specifies input context (256,144 tokens). Only Jamba 1.5 Mini specifies output context (256,144 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
Fri May 08 2026 • llm-stats.com

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Jamba 1.5 Mini uses Jamba Open 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

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Jamba 1.5 Mini was released on 2024-08-22.

Jamba 1.5 Mini is 3 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

1.9 years ago

Jamba 1.5 Mini

Aug 22, 2024

1.7 years ago

2mo newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while Codestral-22B's cutoff date is not specified.

We can confirm Jamba 1.5 Mini's training data extends to 2024-03-05, but cannot make a direct comparison without Codestral-22B's cutoff date.

Codestral-22B

—

Jamba 1.5 Mini

Mar 2024

Outputs Comparison

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Key Takeaways

Mistral AI

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

AI21 Labs
Larger context window (256,144 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
AI21 Labs
Jamba 1.5 Mini

FAQ

Common questions about Codestral-22B vs Jamba 1.5 Mini.

Which is better, Codestral-22B or Jamba 1.5 Mini?

Codestral-22B (Mistral AI) and Jamba 1.5 Mini (AI21 Labs) 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 Jamba 1.5 Mini in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%.

What are the context window sizes for Codestral-22B and Jamba 1.5 Mini?

Codestral-22B supports an unknown number of tokens and Jamba 1.5 Mini supports 256K 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 Jamba 1.5 Mini?

Key differences include licensing (MNPL-0.1 vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and Jamba 1.5 Mini?

Codestral-22B is developed by Mistral AI and Jamba 1.5 Mini is developed by AI21 Labs.