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IBM Granite 4.0 Tiny Preview vs Muse Wonder Full

Muse Wonder Full leads the LLM Stats Score 52.1 to -5.5.

IBM · Meta · Updated for 2026

Which is better?

Muse Wonder Full leads the overall LLM Stats Score 52.1 to -5.5, ranking #13 overall.

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

Choose IBM Granite 4.0 Tiny Preview

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

Choose Muse Wonder Full

  • overall performance matters — it scores 52.1 and ranks #13 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

IBM Granite 4.0 Tiny Preview
IBM
Muse Wonder Full
Meta
Core performance indexes
LLM Stats Score
-5.5
#374
52.1
#13
Reasoning
-5.5
#364
38.4
#71
Coding
2.9
#234
41.5
#8
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—

Individual benchmarks

12 reported for IBM Granite 4.0 Tiny Preview · 16 for Muse Wonder Full

No common benchmarks found

IBM Granite 4.0 Tiny Preview and Muse Wonder Fulldon'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

Input capabilities

Documented input modalities across available providers

Muse Wonder Full supports multimodal inputs, whereas IBM Granite 4.0 Tiny Preview does not.

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

IBM Granite 4.0 Tiny Preview

Text
Images
Audio
Video

Muse Wonder Full

Text
Images
Audio
Video

License

Usage and distribution terms

IBM Granite 4.0 Tiny Preview is licensed under Apache 2.0, while Muse Wonder Full uses a proprietary license.

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

IBM Granite 4.0 Tiny Preview

Apache 2.0

Open weights

Muse Wonder Full

Proprietary

Closed source

Release Timeline

When each model was launched

IBM Granite 4.0 Tiny Preview was released on 2025-05-02, while Muse Wonder Full was released on 2026-10-12.

Muse Wonder Full is 18 months newer than IBM Granite 4.0 Tiny Preview.

IBM Granite 4.0 Tiny Preview

May 2, 2025

1.4 years ago

Muse Wonder Full

Oct 12, 2026

-1 days ago

1.4yr 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 IBM Granite 4.0 Tiny Preview and Muse Wonder Full side-by-side, then vote on the output you prefer.

IBM Granite 4.0 Tiny Preview
✓ Preferred
Muse Wonder Full
Open in Playground

FAQ

Common questions about IBM Granite 4.0 Tiny Preview vs Muse Wonder Full.

Which is better, IBM Granite 4.0 Tiny Preview or Muse Wonder Full?

Muse Wonder Full leads the LLM Stats Score 52.1 to -5.5. IBM Granite 4.0 Tiny Preview is made by IBM and Muse Wonder Full is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does IBM Granite 4.0 Tiny Preview compare to Muse Wonder Full in benchmarks?

IBM Granite 4.0 Tiny Preview scores AttaQ: 86.1%, HumanEval: 82.4%, HumanEval+: 78.3%, GSM8k: 70.1%, IFEval: 63.0%. Muse Wonder Full scores MemoryBench: 85.5%, DeepSWE 1.1: 79.0%, OSWorld 2.1 (partial): 78.4%, JobBench: 75.3%, HealthBench Professional: 62.3%.

What are the main differences between IBM Granite 4.0 Tiny Preview and Muse Wonder Full?

Key differences include LLM Stats Score (-5.5 vs 52.1), multimodal support (no vs yes), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes IBM Granite 4.0 Tiny Preview and Muse Wonder Full?

IBM Granite 4.0 Tiny Preview is developed by IBM and Muse Wonder Full is developed by Meta.

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