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Codestral-22B vs Mistral NeMo Instruct

Codestral-22B and Mistral NeMo Instruct are closely matched at 0.0 and -4.8 on the LLM Stats Score.

Mistral AI · Mistral AI · Updated for 2026

Which is better?

Codestral-22B and Mistral NeMo Instruct are closely matched on the overall LLM Stats Score at 0.0 and -4.8.

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 Mistral NeMo Instruct

  • you want the most recent training data — it shipped Jul 2024

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
Mistral NeMo Instruct
Mistral AI
Core performance indexes
LLM Stats Score
0.0
#326
-4.8
#353
Reasoning
-0.1
#318
-5.0
#345
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.02 / M
Output price
— / M
$0.03 / M
Context window
—
131,072

Individual benchmarks

7 reported for Codestral-22B · 8 for Mistral NeMo Instruct

No common benchmarks found

Codestral-22B and Mistral NeMo Instructdon'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

10.2B diff

Codestral-22B has 10.2B more parameters than Mistral NeMo Instruct, making it 85.0% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
22.2B
Codestral-22B
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

Only Mistral NeMo Instruct specifies input context (131,072 tokens). Only Mistral NeMo Instruct specifies output context (131,072 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Mistral AI
Mistral NeMo Instruct
Input131,072 tokens
Output131,072 tokens
Thu Sep 17 2026 • llm-stats.com

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Mistral NeMo Instruct uses Apache 2.0.

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

Codestral-22B

MNPL-0.1

Open weights

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Mistral NeMo Instruct was released on 2024-07-18.

Mistral NeMo Instruct is 2 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.3 years ago

Mistral NeMo Instruct

Jul 18, 2024

2.2 years ago

1mo 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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Codestral-22B and Mistral NeMo Instruct side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Mistral NeMo Instruct
Open in Playground

FAQ

Common questions about Codestral-22B vs Mistral NeMo Instruct.

Which is better, Codestral-22B or Mistral NeMo Instruct?

Codestral-22B and Mistral NeMo Instruct are closely matched on the LLM Stats Score at 0.0 and -4.8. Codestral-22B is made by Mistral AI and Mistral NeMo Instruct is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Codestral-22B compare to Mistral NeMo Instruct in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.

What are the context window sizes for Codestral-22B and Mistral NeMo Instruct?

Codestral-22B supports an unknown number of tokens and Mistral NeMo Instruct supports 131K 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 Mistral NeMo Instruct?

Key differences include LLM Stats Score (0.0 vs -4.8), licensing (MNPL-0.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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