Model Comparison
Llama 3.2 90B Instruct vs Muse Spark 1.1Which is better in 2026?
Comparing Llama 3.2 90B Instruct and Muse Spark 1.1 across benchmarks, pricing, and capabilities.
Verdict: Llama 3.2 90B Instruct vs Muse Spark 1.1 — which is better?
Llama 3.2 90B Instruct (by Meta) and Muse Spark 1.1 (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, Llama 3.2 90B Instruct is roughly 5.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark 1.1 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Llama 3.2 90B Instruct if…
- cost matters — it's about 5.5x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Muse Spark 1.1 if…
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Performance Benchmarks
Comparative analysis across standard metrics
Llama 3.2 90B Instruct and Muse Spark 1.1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 3.2 90B Instruct ($0.35/1M tokens) is 3.6x cheaper than Muse Spark 1.1 ($1.25/1M tokens).
For output processing, Llama 3.2 90B Instruct ($0.40/1M tokens) is 10.6x cheaper than Muse Spark 1.1 ($4.25/1M tokens).
In conclusion, Muse Spark 1.1 is more expensive than Llama 3.2 90B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.1 accepts 1,048,576 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. Muse Spark 1.1 can generate longer responses up to 131,072 tokens, while Llama 3.2 90B Instruct is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Both Llama 3.2 90B Instruct and Muse Spark 1.1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Llama 3.2 90B Instruct
Muse Spark 1.1
License
Usage and distribution terms
Llama 3.2 90B Instruct is licensed under Llama 3.2, while Muse Spark 1.1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.2
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Llama 3.2 90B Instruct was released on 2024-09-25, while Muse Spark 1.1 was released on 2026-07-09.
Muse Spark 1.1 is 22 months newer than Llama 3.2 90B Instruct.
Sep 25, 2024
1.8 years ago
Jul 9, 2026
1 weeks ago
1.8yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic. Muse Spark 1.1 is available from Meta Model API.
Llama 3.2 90B Instruct
Muse Spark 1.1
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Llama 3.2 90B Instruct and Muse Spark 1.1 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Llama 3.2 90B Instruct vs Muse Spark 1.1.