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Gemma 3 27B vs Muse Wonder

Muse Wonder leads the LLM Stats Score 47.9 to 8.3. Gemma 3 27B is 80.0x cheaper per token.

Google · Meta · Updated for 2026

Which is better?

Muse Wonder leads the overall LLM Stats Score 47.9 to 8.3, ranking #29 overall.

On price, Gemma 3 27B is roughly 80.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

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

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

Choose Gemma 3 27B

  • cost matters — it's about 80.0x cheaper per token
  • 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 and coding — it leads those capability indexes
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Core performance indexes
8.3
#296
47.9
#29
8.6
#287
33.1
#109
5.3
#213
38.9
#18
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.08 / M
$4.00 / M
Output price
$0.16 / M
$20.00 / M
Context window
131,072
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemma 3 27B
Muse Wonder
-3.3#206
25.4#52
-0.9#169
25.4#52
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

27 reported for Gemma 3 27B · 16 for Muse Wonder

No common benchmarks found

Gemma 3 27B 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

Pricing Analysis

Price comparison per million tokens

Gemma 3 27B costs less

For input processing, Gemma 3 27B ($0.08/1M tokens) is 50.0x cheaper than Muse Wonder ($4.00/1M tokens).

For output processing, Gemma 3 27B ($0.16/1M tokens) is 125.0x cheaper than Muse Wonder ($20.00/1M tokens).

In conclusion, Muse Wonder is more expensive than Gemma 3 27B.*

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

Lowest available price from all providers
Thu Oct 15 2026 • llm-stats.com
Google
Gemma 3 27B
Input tokens$0.08
Output tokens$0.16
Best providerDeepinfra
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

Muse Wonder accepts 1,048,576 input tokens compared to Gemma 3 27B's 131,072 tokens. Only Gemma 3 27B specifies output context (131,072 tokens).

Google
Gemma 3 27B
Input131,072 tokens
Output131,072 tokens
Meta
Muse Wonder
Input1,048,576 tokens
Output- tokens
Thu Oct 15 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemma 3 27B and Muse Wonder support multimodal inputs.

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

Gemma 3 27B

Text
Images
Audio
Video

Muse Wonder

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3 27B is licensed under Gemma, while Muse Wonder uses a proprietary license.

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

Gemma 3 27B

Gemma

Open weights

Muse Wonder

Proprietary

Closed source

Release Timeline

When each model was launched

Gemma 3 27B was released on 2025-03-12, while Muse Wonder was released on 2026-10-12.

Muse Wonder is 19 months newer than Gemma 3 27B.

Gemma 3 27B

Mar 12, 2025

1.6 years ago

Muse Wonder

Oct 12, 2026

0 days ago

1.6yr 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

Gemma 3 27B is available from DeepInfra, Novita. Muse Wonder is available from Meta Model API.

Gemma 3 27B

deepinfra logo
Deepinfra
Input Price:Input: $0.08/1MOutput Price:Output: $0.16/1M
novita logo
Novita
Input Price:Input: $0.11/1MOutput Price:Output: $0.20/1M

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 Gemma 3 27B and Muse Wonder side-by-side, then vote on the output you prefer.

Gemma 3 27B
✓ Preferred
Muse Wonder
Open in Playground

FAQ

Common questions about Gemma 3 27B vs Muse Wonder.

Which is better, Gemma 3 27B or Muse Wonder?

Muse Wonder leads the LLM Stats Score 47.9 to 8.3. Gemma 3 27B is made by Google 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 Gemma 3 27B compare to Muse Wonder in benchmarks?

Gemma 3 27B scores GSM8k: 95.9%, IFEval: 90.4%, MATH: 89.0%, HumanEval: 87.8%, BIG-Bench Hard: 87.6%. 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 Gemma 3 27B cheaper than Muse Wonder?

Gemma 3 27B is 50.0x cheaper for input tokens. Gemma 3 27B costs $0.08/M input and $0.16/M output via deepinfra. Muse Wonder costs $4.00/M input and $20.00/M output via meta.

What are the context window sizes for Gemma 3 27B and Muse Wonder?

Gemma 3 27B supports 131K 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 Gemma 3 27B and Muse Wonder?

Key differences include LLM Stats Score (8.3 vs 47.9), context window (131K vs 1.0M), input pricing ($0.08 vs $4.00/M), licensing (Gemma vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3 27B and Muse Wonder?

Gemma 3 27B is developed by Google and Muse Wonder is developed by Meta.