Model Comparison

Muse Spark 1.1 vs Sarvam-30BWhich is better in 2026?

Comparing Muse Spark 1.1 and Sarvam-30B across benchmarks, pricing, and capabilities.

Verdict: Muse Spark 1.1 vs Sarvam-30B — which is better?

Muse Spark 1.1 (by Meta) and Sarvam-30B (by Sarvam AI) 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 Muse Spark 1.1 if…

  • you want the most recent training data — it shipped Jul 2026

Choose Sarvam-30B if…

  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Muse Spark 1.1 and Sarvam-30Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Muse Spark 1.1 specifies input context (1,048,576 tokens). Only Muse Spark 1.1 specifies output context (131,072 tokens).

Meta
Muse Spark 1.1
Input1,048,576 tokens
Output131,072 tokens
Sarvam AI
Sarvam-30B
Input- tokens
Output- tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Muse Spark 1.1 supports multimodal inputs, whereas Sarvam-30B does not.

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

Muse Spark 1.1

Text
Images
Audio
Video

Sarvam-30B

Text
Images
Audio
Video

License

Usage and distribution terms

Muse Spark 1.1 is licensed under a proprietary license, while Sarvam-30B uses Apache 2.0.

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

Muse Spark 1.1

Proprietary

Closed source

Sarvam-30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Muse Spark 1.1 was released on 2026-07-09, while Sarvam-30B was released on 2026-03-06.

Muse Spark 1.1 is 4 months newer than Sarvam-30B.

Muse Spark 1.1

Jul 9, 2026

1 weeks ago

4mo newer
Sarvam-30B

Mar 6, 2026

4 months 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Meta
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Sarvam AI
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Muse Spark 1.1 and Sarvam-30B side-by-side, then vote on the output you prefer.

Muse Spark 1.1
✓ Preferred
Sarvam-30B
Open in Playground
AI Model Comparison Table
Feature
Meta
Muse Spark 1.1
Sarvam AI
Sarvam-30B

FAQ

Common questions about Muse Spark 1.1 vs Sarvam-30B.

Which is better, Muse Spark 1.1 or Sarvam-30B?

Muse Spark 1.1 (Meta) and Sarvam-30B (Sarvam AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Muse Spark 1.1 compare to Sarvam-30B in benchmarks?

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%. Sarvam-30B scores MATH-500: 97.0%, AIME 2025: 96.7%, MBPP: 92.7%, HumanEval: 92.1%, MMLU: 85.1%.

What are the context window sizes for Muse Spark 1.1 and Sarvam-30B?

Muse Spark 1.1 supports 1.0M tokens and Sarvam-30B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Muse Spark 1.1 and Sarvam-30B?

Key differences include multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Muse Spark 1.1 and Sarvam-30B?

Muse Spark 1.1 is developed by Meta and Sarvam-30B is developed by Sarvam AI.

Related comparisons