Model Comparison

Devstral Small 1.1 vs Muse Spark 1.1Which is better in 2026?

Comparing Devstral Small 1.1 and Muse Spark 1.1 across benchmarks, pricing, and capabilities.

Verdict: Devstral Small 1.1 vs Muse Spark 1.1 — which is better?

Devstral Small 1.1 (by Mistral AI) and Muse Spark 1.1 (by Meta) 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.

On price, Devstral Small 1.1 is roughly 13.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Muse Spark 1.1 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose Devstral Small 1.1 if…

  • cost matters — it's about 13.3x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose Muse Spark 1.1 if…

  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Devstral Small 1.1 and Muse Spark 1.1don'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

Devstral Small 1.1 costs less

For input processing, Devstral Small 1.1 ($0.10/1M tokens) is 12.5x cheaper than Muse Spark 1.1 ($1.25/1M tokens).

For output processing, Devstral Small 1.1 ($0.30/1M tokens) is 14.2x cheaper than Muse Spark 1.1 ($4.25/1M tokens).

In conclusion, Muse Spark 1.1 is more expensive than Devstral Small 1.1.*

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

Lowest available price from all providers
Sun Jul 26 2026 • llm-stats.com
Mistral AI
Devstral Small 1.1
Input tokens$0.10
Output tokens$0.30
Best providerMistral
Meta
Muse Spark 1.1
Input tokens$1.25
Output tokens$4.25
Best providerMeta
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Muse Spark 1.1 accepts 1,048,576 input tokens compared to Devstral Small 1.1's 128,000 tokens. Muse Spark 1.1 can generate longer responses up to 131,072 tokens, while Devstral Small 1.1 is limited to 128,000 tokens.

Mistral AI
Devstral Small 1.1
Input128,000 tokens
Output128,000 tokens
Meta
Muse Spark 1.1
Input1,048,576 tokens
Output131,072 tokens
Sun Jul 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Muse Spark 1.1 supports multimodal inputs, whereas Devstral Small 1.1 does not.

Muse Spark 1.1 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Devstral Small 1.1

Text
Images
Audio
Video

Muse Spark 1.1

Text
Images
Audio
Video

License

Usage and distribution terms

Devstral Small 1.1 is licensed under Apache 2.0, while Muse Spark 1.1 uses a proprietary license.

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

Devstral Small 1.1

Apache 2.0

Open weights

Muse Spark 1.1

Proprietary

Closed source

Release Timeline

When each model was launched

Devstral Small 1.1 was released on 2025-07-11, while Muse Spark 1.1 was released on 2026-07-09.

Muse Spark 1.1 is 12 months newer than Devstral Small 1.1.

Devstral Small 1.1

Jul 11, 2025

1.0 years ago

Muse Spark 1.1

Jul 9, 2026

2 weeks ago

12mo 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

Provider Availability

Devstral Small 1.1 is available from Mistral AI. Muse Spark 1.1 is available from Meta Model API.

Devstral Small 1.1

mistral logo
Mistral
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M

Muse Spark 1.1

meta logo
Meta
Input Price:Input: $1.25/1MOutput Price:Output: $4.25/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Mistral AI
Less expensive input tokens
Less expensive output tokens
Has open weights
Meta
Larger context window (1,048,576 tokens)
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Devstral Small 1.1 and Muse Spark 1.1 side-by-side, then vote on the output you prefer.

Devstral Small 1.1
✓ Preferred
Muse Spark 1.1
Open in Playground
AI Model Comparison Table
Feature
Mistral AI
Devstral Small 1.1
Meta
Muse Spark 1.1

FAQ

Common questions about Devstral Small 1.1 vs Muse Spark 1.1.

Which is better, Devstral Small 1.1 or Muse Spark 1.1?

Devstral Small 1.1 (Mistral AI) and Muse Spark 1.1 (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Devstral Small 1.1 compare to Muse Spark 1.1 in benchmarks?

Devstral Small 1.1 scores SWE-Bench Verified: 53.6%. Muse Spark 1.1 scores CharXiv-R: 88.4%, MCP Atlas: 88.1%, OSWorld-Verified: 80.8%, Terminal-Bench 2.1: 80.0%, BabyVision: 76.3%.

Is Devstral Small 1.1 cheaper than Muse Spark 1.1?

Devstral Small 1.1 is 12.5x cheaper for input tokens. Devstral Small 1.1 costs $0.10/M input and $0.30/M output via mistral. Muse Spark 1.1 costs $1.25/M input and $4.25/M output via meta.

What are the context window sizes for Devstral Small 1.1 and Muse Spark 1.1?

Devstral Small 1.1 supports 128K tokens and Muse Spark 1.1 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Devstral Small 1.1 and Muse Spark 1.1?

Key differences include context window (128K vs 1.0M), input pricing ($0.10 vs $1.25/M), multimodal support (no vs yes), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Devstral Small 1.1 and Muse Spark 1.1?

Devstral Small 1.1 is developed by Mistral AI and Muse Spark 1.1 is developed by Meta.

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