Gemma 4 31B vs Muse Spark 1.3
Muse Spark 1.3 leads the LLM Stats Score 55.3 to 33.2. Muse Spark 1.3 is 1.5x cheaper per token.
Google · Meta · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 55.3 to 33.2, ranking #5 overall.
In the 1 individual benchmarks reported for both models, Muse Spark 1.3 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Muse Spark 1.3 is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark 1.3 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
- you need open weights you can self-host or fine-tune
Choose Muse Spark 1.3
- overall performance matters — it scores 55.3 and ranks #5 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 1.5x 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 Sep 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 · 11 for Muse Spark 1.3
Gemma 4 31B outperforms in 0 benchmarks, while Muse Spark 1.3 is better at 1 benchmark (MRCR v2 (8-needle)).
Muse Spark 1.3 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 ($0.13/1M tokens) is 1.3x more expensive than Muse Spark 1.3 ($0.10/1M tokens).
For output processing, Gemma 4 31B ($0.38/1M tokens) is 1.9x more expensive than Muse Spark 1.3 ($0.20/1M tokens).
In conclusion, Gemma 4 31B is more expensive than Muse Spark 1.3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.3 accepts 1,048,576 input tokens compared to Gemma 4 31B's 262,144 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while Gemma 4 31B is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 4 31B and Muse Spark 1.3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 4 31B
Muse Spark 1.3
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while Muse Spark 1.3 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 4 31B was released on 2026-04-02, while Muse Spark 1.3 was released on 2026-09-02.
Muse Spark 1.3 is 5 months newer than Gemma 4 31B.
Apr 2, 2026
5 months ago
Sep 2, 2026
3 days ago
5mo newerKnowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Muse Spark 1.3'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 1.3's cutoff date.
Jan 2025
—
Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. Muse Spark 1.3 is available from Meta Model API.
Gemma 4 31B
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 4 31B and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 4 31B vs Muse Spark 1.3.