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Muse Spark Open vs Muse Wonder

Muse Wonder leads the LLM Stats Score 49.7 to 44.9. Muse Spark Open is 4.0x cheaper per token.

Meta · Meta · Updated for 2026

Which is better?

Muse Wonder leads the overall LLM Stats Score 49.7 to 44.9, ranking #22 overall.

In the 2 individual benchmarks reported for both models, Muse Wonder wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, Muse Spark Open is roughly 4.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

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

Choose Muse Spark Open

  • cost matters — it's about 4.0x cheaper per token
  • you want the most recent training data — it shipped Oct 2026
  • you need open weights you can self-host or fine-tune

Choose Muse Wonder

  • overall performance matters — it scores 49.7 and ranks #22 on LLM Stats
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results

At a glance

The differences that matter most.

Muse Spark Open
Meta
Muse Wonder
Meta
Core performance indexes
LLM Stats Score
44.9
#43
49.7
#22
Reasoning
45.2
#39
42.4
#57
Coding
33.0
#42
39.5
#12
Agents
30.6
#43
37.6
#14
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$1.25 / M
$4.00 / M
Output price
$4.25 / M
$20.00 / M
Context window
1,048,576
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Muse Spark Open
Muse Wonder
Vision
31.2#34
26.6#52
Tool use
23.3#44
22.4#54
Multimodal
33.1#20
26.6#52
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

17 reported for Muse Spark Open · 18 for Muse Wonder

2 shared

Muse Spark Open outperforms in 0 benchmarks, while Muse Wonder is better at 2 benchmarks (Artificial Analysis, DeepSWE 1.1).

Muse Wonder significantly outperforms across most benchmarks.

Mon Oct 19 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Muse Spark Open costs less

For input processing, Muse Spark Open ($1.25/1M tokens) is 3.2x cheaper than Muse Wonder ($4.00/1M tokens).

For output processing, Muse Spark Open ($4.25/1M tokens) is 4.7x cheaper than Muse Wonder ($20.00/1M tokens).

In conclusion, Muse Wonder is more expensive than Muse Spark Open.*

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

Lowest available price from all providers
Mon Oct 19 2026 • llm-stats.com
Meta
Muse Spark Open
Input tokens$1.25
Output tokens$4.25
Best providerTogether
Meta
Muse Wonder
Input tokens$4.00
Output tokens$20.00
Best providerMeta
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. Only Muse Spark Open specifies output context (1,048,576 tokens).

Meta
Muse Spark Open
Input1,048,576 tokens
Output1,048,576 tokens
Meta
Muse Wonder
Input1,048,576 tokens
Output- tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Muse Spark Open and Muse Wonder support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Muse Spark Open

Text
Images
Audio
Video

Muse Wonder

Text
Images
Audio
Video

License

Usage and distribution terms

Muse Spark Open is licensed under Muse Model License, while Muse Wonder uses a proprietary license.

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

Muse Spark Open

Muse Model License

Open weights

Muse Wonder

Proprietary

Closed source

Release Timeline

When each model was launched

Muse Spark Open was released on 2026-10-15, while Muse Wonder was released on 2026-10-12.

Muse Spark Open is 0 month newer than Muse Wonder.

Muse Spark Open

Oct 15, 2026

2 days ago

3d newer
Muse Wonder

Oct 12, 2026

5 days 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

Muse Spark Open is available from Together. Muse Wonder is available from Meta Model API.

Muse Spark Open

together logo
Together
Input Price:Input: $1.25/1MOutput Price:Output: $4.25/1M

Muse Wonder

meta logo
Meta
Input Price:Input: $4.00/1MOutput Price:Output: $20.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

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

Muse Spark Open
✓ Preferred
Muse Wonder
Open in Playground

FAQ

Common questions about Muse Spark Open vs Muse Wonder.

Which is better, Muse Spark Open or Muse Wonder?

Muse Wonder leads the LLM Stats Score 49.7 to 44.9. Muse Spark Open is made by Meta 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 Muse Spark Open compare to Muse Wonder in benchmarks?

Muse Spark Open scores MCP Atlas: 89.2%, GPQA: 89.0%, OSWorld-Verified: 80.4%, BabyVision: 80.2%, Terminal-Bench 2.1: 76.4%. Muse Wonder scores MemoryBench: 85.6%, DeepSWE 1.1: 78.8%, OSWorld 2.1 (partial): 72.6%, JobBench: 70.5%, HealthBench Professional: 60.5%.

Is Muse Spark Open cheaper than Muse Wonder?

Muse Spark Open is 3.2x cheaper for input tokens. Muse Spark Open costs $1.25/M input and $4.25/M output via together. Muse Wonder costs $4.00/M input and $20.00/M output via meta.

What are the context window sizes for Muse Spark Open and Muse Wonder?

Muse Spark Open supports 1.0M 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 Muse Spark Open and Muse Wonder?

Key differences include LLM Stats Score (44.9 vs 49.7), input pricing ($1.25 vs $4.00/M), licensing (Muse Model License vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

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