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MiniCPM-SALA vs Muse Wonder

Muse Wonder leads the LLM Stats Score 47.9 to 14.4.

OpenBMB · Meta · Updated for 2026

Which is better?

Muse Wonder leads the overall LLM Stats Score 47.9 to 14.4, ranking #29 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose MiniCPM-SALA

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

Choose Muse Wonder

  • overall performance matters — it scores 47.9 and ranks #29 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Core performance indexes
14.4
#252
47.9
#29
15.7
#237
33.1
#108
20.9
#102
38.9
#18
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$4.00 / M
Output price
— / M
$20.00 / M
Context window
—
1,048,576

Individual benchmarks

24 reported for MiniCPM-SALA · 16 for Muse Wonder

No common benchmarks found

MiniCPM-SALA and Muse Wonderdon'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

Context Window

Maximum input and output token capacity

Only Muse Wonder specifies input context (1,048,576 tokens).

OpenBMB
MiniCPM-SALA
Input- tokens
Output- tokens
Meta
Muse Wonder
Input1,048,576 tokens
Output- tokens
Wed Oct 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Muse Wonder supports multimodal inputs, whereas MiniCPM-SALA does not.

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

MiniCPM-SALA

Text
Images
Audio
Video

Muse Wonder

Text
Images
Audio
Video

License

Usage and distribution terms

MiniCPM-SALA is licensed under Apache 2.0, while Muse Wonder uses a proprietary license.

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

MiniCPM-SALA

Apache 2.0

Open weights

Muse Wonder

Proprietary

Closed source

Release Timeline

When each model was launched

MiniCPM-SALA was released on 2026-02-11, while Muse Wonder was released on 2026-10-12.

Muse Wonder is 8 months newer than MiniCPM-SALA.

MiniCPM-SALA

Feb 11, 2026

8 months ago

Muse Wonder

Oct 12, 2026

1 days ago

8mo 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?

Judge for yourself.

Run your own prompts against MiniCPM-SALA and Muse Wonder side-by-side, then vote on the output you prefer.

MiniCPM-SALA
✓ Preferred
Muse Wonder
Open in Playground

FAQ

Common questions about MiniCPM-SALA vs Muse Wonder.

Which is better, MiniCPM-SALA or Muse Wonder?

Muse Wonder leads the LLM Stats Score 47.9 to 14.4. MiniCPM-SALA is made by OpenBMB and Muse Wonder is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does MiniCPM-SALA compare to Muse Wonder in benchmarks?

MiniCPM-SALA scores HumanEval: 95.1%, RULER 64k: 92.7%, RULER 128k: 89.4%, MBPP: 89.1%, RULER 512K: 87.1%. Muse Wonder scores MemoryBench: 85.6%, DeepSWE 1.1: 78.8%, OSWorld 2.1 (partial): 72.6%, JobBench: 70.5%, HealthBench Professional: 60.5%.

What are the context window sizes for MiniCPM-SALA and Muse Wonder?

MiniCPM-SALA supports an unknown number of tokens and Muse Wonder 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 MiniCPM-SALA and Muse Wonder?

Key differences include LLM Stats Score (14.4 vs 47.9), multimodal support (no vs yes), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes MiniCPM-SALA and Muse Wonder?

MiniCPM-SALA is developed by OpenBMB and Muse Wonder is developed by Meta.