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Llama 3.2 3B Instruct vs Muse Wonder

Muse Wonder leads the LLM Stats Score 47.9 to -6.1. Llama 3.2 3B Instruct is 640.0x cheaper per token.

Meta · Meta · Updated for 2026

Which is better?

Muse Wonder leads the overall LLM Stats Score 47.9 to -6.1, ranking #29 overall.

On price, Llama 3.2 3B Instruct is roughly 640.0x 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 Llama 3.2 3B Instruct

  • cost matters — it's about 640.0x 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 — 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
-6.1
#376
47.9
#29
-6.7
#370
33.1
#108
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.01 / M
$4.00 / M
Output price
$0.02 / M
$20.00 / M
Context window
128,000
1,048,576

Individual benchmarks

15 reported for Llama 3.2 3B Instruct · 16 for Muse Wonder

No common benchmarks found

Llama 3.2 3B Instruct 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

Llama 3.2 3B Instruct costs less

For input processing, Llama 3.2 3B Instruct ($0.01/1M tokens) is 400.0x cheaper than Muse Wonder ($4.00/1M tokens).

For output processing, Llama 3.2 3B Instruct ($0.02/1M tokens) is 1000.0x cheaper than Muse Wonder ($20.00/1M tokens).

In conclusion, Muse Wonder is more expensive than Llama 3.2 3B Instruct.*

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

Lowest available price from all providers
Wed Oct 14 2026 • llm-stats.com
Meta
Llama 3.2 3B Instruct
Input tokens$0.01
Output tokens$0.02
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 Llama 3.2 3B Instruct's 128,000 tokens. Only Llama 3.2 3B Instruct specifies output context (128,000 tokens).

Meta
Llama 3.2 3B Instruct
Input128,000 tokens
Output128,000 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 Llama 3.2 3B Instruct does not.

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

Llama 3.2 3B Instruct

Text
Images
Audio
Video

Muse Wonder

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.2 3B Instruct is licensed under Llama 3.2 Community License, while Muse Wonder uses a proprietary license.

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

Llama 3.2 3B Instruct

Llama 3.2 Community License

Open weights

Muse Wonder

Proprietary

Closed source

Release Timeline

When each model was launched

Llama 3.2 3B Instruct was released on 2024-09-25, while Muse Wonder was released on 2026-10-12.

Muse Wonder is 25 months newer than Llama 3.2 3B Instruct.

Llama 3.2 3B Instruct

Sep 25, 2024

2.0 years ago

Muse Wonder

Oct 12, 2026

-1 days ago

2.0yr 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

Llama 3.2 3B Instruct is available from DeepInfra. Muse Wonder is available from Meta Model API.

Llama 3.2 3B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.01/1MOutput Price:Output: $0.02/1M

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 Llama 3.2 3B Instruct and Muse Wonder side-by-side, then vote on the output you prefer.

Llama 3.2 3B Instruct
✓ Preferred
Muse Wonder
Open in Playground

FAQ

Common questions about Llama 3.2 3B Instruct vs Muse Wonder.

Which is better, Llama 3.2 3B Instruct or Muse Wonder?

Muse Wonder leads the LLM Stats Score 47.9 to -6.1. Llama 3.2 3B Instruct 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 Llama 3.2 3B Instruct compare to Muse Wonder in benchmarks?

Llama 3.2 3B Instruct scores NIH/Multi-needle: 84.7%, ARC-C: 78.6%, GSM8k: 77.7%, IFEval: 77.4%, HellaSwag: 69.8%. 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 Llama 3.2 3B Instruct cheaper than Muse Wonder?

Llama 3.2 3B Instruct is 400.0x cheaper for input tokens. Llama 3.2 3B Instruct costs $0.01/M input and $0.02/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 Llama 3.2 3B Instruct and Muse Wonder?

Llama 3.2 3B Instruct supports 128K 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 Llama 3.2 3B Instruct and Muse Wonder?

Key differences include LLM Stats Score (-6.1 vs 47.9), context window (128K vs 1.0M), input pricing ($0.01 vs $4.00/M), multimodal support (no vs yes), licensing (Llama 3.2 Community License vs Proprietary). See the full comparison above for benchmark-by-benchmark results.