Model Comparison

Devstral Medium vs Mistral NeMo Instruct

Comparing Devstral Medium and Mistral NeMo Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Devstral Medium and Mistral NeMo Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Mistral NeMo Instruct costs less

For input processing, Devstral Medium ($0.40/1M tokens) is 2.7x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

For output processing, Devstral Medium ($2.00/1M tokens) is 13.3x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

In conclusion, Devstral Medium is more expensive than Mistral NeMo Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
Mistral AI
Devstral Medium
Input tokens$0.40
Output tokens$2.00
Best providerMistral
Mistral AI
Mistral NeMo Instruct
Input tokens$0.15
Output tokens$0.15
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.

Mistral AI
Devstral Medium
Input128,000 tokens
Output128,000 tokens
Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Wed Apr 22 2026 • llm-stats.com

License

Usage and distribution terms

Devstral Medium is licensed under a proprietary license, while Mistral NeMo Instruct uses Apache 2.0.

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

Devstral Medium

Proprietary

Closed source

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Devstral Medium was released on 2025-07-10, while Mistral NeMo Instruct was released on 2024-07-18.

Devstral Medium is 12 months newer than Mistral NeMo Instruct.

Devstral Medium

Jul 10, 2025

9 months ago

11mo newer
Mistral NeMo Instruct

Jul 18, 2024

1.8 years ago

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

Provider Availability

Devstral Medium is available from Mistral AI. Mistral NeMo Instruct is available from Google, Mistral AI.

Devstral Medium

mistral logo
Mistral
Input Price:Input: $0.40/1MOutput Price:Output: $2.00/1M

Mistral NeMo Instruct

google logo
Google
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
mistral logo
Mistral
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Mistral AI
Mistral AI
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Devstral Medium
Mistral AI
Mistral NeMo Instruct

FAQ

Common questions about Devstral Medium vs Mistral NeMo Instruct

Devstral Medium (Mistral AI) and Mistral NeMo Instruct (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Devstral Medium scores SWE-Bench Verified: 61.6%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.
Mistral NeMo Instruct is 2.7x cheaper for input tokens. Devstral Medium costs $0.40/M input and $2.00/M output via mistral. Mistral NeMo Instruct costs $0.15/M input and $0.15/M output via google.
Devstral Medium supports 128K tokens and Mistral NeMo Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($0.40 vs $0.15/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.