Gemma 4 31B vs Muse Spark Open
Muse Spark Open leads the LLM Stats Score 44.9 to 33.0. Gemma 4 31B is 13.1x cheaper per token.
Google · Meta · Updated for 2026
Which is better?
Muse Spark Open leads the overall LLM Stats Score 44.9 to 33.0, ranking #43 overall.
In the 1 individual benchmarks reported for both models, Muse Spark Open wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 4 31B is roughly 13.1x 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 Gemma 4 31B
- cost matters — it's about 13.1x cheaper per token
Choose Muse Spark Open
- overall performance matters — it scores 44.9 and ranks #43 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for Gemma 4 31B · 17 for Muse Spark Open
Gemma 4 31B outperforms in 0 benchmarks, while Muse Spark Open is better at 1 benchmark (GPQA).
Muse Spark Open significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 4 31B ($0.09/1M tokens) is 13.9x cheaper than Muse Spark Open ($1.25/1M tokens).
For output processing, Gemma 4 31B ($0.34/1M tokens) is 12.5x cheaper than Muse Spark Open ($4.25/1M tokens).
In conclusion, Muse Spark Open is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Muse Spark Open has 785.3B more parameters than Gemma 4 31B, making it 2558.0% larger.
Context Window
Maximum input and output token capacity
Muse Spark Open accepts 1,048,576 input tokens compared to Gemma 4 31B's 262,144 tokens. Muse Spark Open can generate longer responses up to 1,048,576 tokens, while Gemma 4 31B is limited to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 4 31B and Muse Spark Open support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 4 31B
Muse Spark Open
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while Muse Spark Open uses Muse Model License.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Muse Model License
Open weights
Release Timeline
When each model was launched
Gemma 4 31B was released on 2026-04-02, while Muse Spark Open was released on 2026-10-15.
Muse Spark Open is 7 months newer than Gemma 4 31B.
Apr 2, 2026
6 months ago
Oct 15, 2026
4 days ago
6mo newerKnowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Muse Spark Open's cutoff date is not specified.
We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without Muse Spark Open's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. Muse Spark Open is available from Together.
Gemma 4 31B
Muse Spark Open
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 4 31B and Muse Spark Open side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 4 31B vs Muse Spark Open.