Gemini 3.1 Pro vs Muse Spark Open
Gemini 3.1 Pro and Muse Spark Open are closely matched at 43.0 and 45.3 on the LLM Stats Score. Muse Spark Open is 2.3x cheaper per token.
Google · Meta · Updated for 2026
Which is better?
Gemini 3.1 Pro and Muse Spark Open are closely matched on the overall LLM Stats Score at 43.0 and 45.3.
The models split the 4 individual benchmarks reported for both models evenly.
On price, Muse Spark Open is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark Open 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 Gemini 3.1 Pro
- you want predictable pricing at $2.00/M input and $12.00/M output
Choose Muse Spark Open
- your work emphasizes agents — it leads those capability indexes
- cost matters — it's about 2.3x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for Gemini 3.1 Pro · 17 for Muse Spark Open
Gemini 3.1 Pro outperforms in 2 benchmarks (GPQA, SciCode), while Muse Spark Open is better at 2 benchmarks (DeepSWE 1.1, MCP Atlas).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.1 Pro ($2.00/1M tokens) is 1.6x more expensive than Muse Spark Open ($1.25/1M tokens).
For output processing, Gemini 3.1 Pro ($12.00/1M tokens) is 2.8x more expensive than Muse Spark Open ($4.25/1M tokens).
In conclusion, Gemini 3.1 Pro is more expensive than Muse Spark Open.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark Open accepts 1,048,576 input tokens compared to Gemini 3.1 Pro's 1,000,000 tokens. Muse Spark Open can generate longer responses up to 1,048,576 tokens, while Gemini 3.1 Pro is limited to 1,000,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 3.1 Pro and Muse Spark Open support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 3.1 Pro
Muse Spark Open
License
Usage and distribution terms
Gemini 3.1 Pro is licensed under a proprietary license, while Muse Spark Open uses Muse Model License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Muse Model License
Open weights
Release Timeline
When each model was launched
Gemini 3.1 Pro was released on 2026-02-19, while Muse Spark Open was released on 2026-10-15.
Muse Spark Open is 8 months newer than Gemini 3.1 Pro.
Feb 19, 2026
8 months ago
Oct 15, 2026
4 days ago
7mo newerKnowledge Cutoff
When training data ends
Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while Muse Spark Open's cutoff date is not specified.
We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without Muse Spark Open's cutoff date.
Jan 2025
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Provider Availability
Gemini 3.1 Pro is available from DeepInfra, Google. Muse Spark Open is available from Together.
Gemini 3.1 Pro
Muse Spark Open
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 3.1 Pro and Muse Spark Open side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 3.1 Pro vs Muse Spark Open.