GPT-5.4 nano vs Muse Spark 1.3
Muse Spark 1.3 leads the LLM Stats Score 53.8 to 26.6. GPT-5.4 nano is 4.3x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 53.8 to 26.6, ranking #8 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, GPT-5.4 nano is roughly 4.3x 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 GPT-5.4 nano
- cost matters — it's about 4.3x cheaper per token
Choose Muse Spark 1.3
- overall performance matters — it scores 53.8 and ranks #8 on LLM Stats
- your work emphasizes reasoning and coding — 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 Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for GPT-5.4 nano · 11 for Muse Spark 1.3
GPT-5.4 nano 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, GPT-5.4 nano ($0.20/1M tokens) is 6.3x cheaper than Muse Spark 1.3 ($1.25/1M tokens).
For output processing, GPT-5.4 nano ($1.25/1M tokens) is 3.4x cheaper than Muse Spark 1.3 ($4.25/1M tokens).
In conclusion, Muse Spark 1.3 is more expensive than GPT-5.4 nano.*
* 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 GPT-5.4 nano's 400,000 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while GPT-5.4 nano is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.4 nano and Muse Spark 1.3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.4 nano
Muse Spark 1.3
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-5.4 nano was released on 2026-03-17, while Muse Spark 1.3 was released on 2026-09-02.
Muse Spark 1.3 is 6 months newer than GPT-5.4 nano.
Mar 17, 2026
6 months ago
Sep 2, 2026
2 weeks ago
5mo newerKnowledge Cutoff
When training data ends
GPT-5.4 nano has a documented knowledge cutoff of 2025-08-31, while Muse Spark 1.3's cutoff date is not specified.
We can confirm GPT-5.4 nano's training data extends to 2025-08-31, but cannot make a direct comparison without Muse Spark 1.3's cutoff date.
Aug 2025
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Provider Availability
GPT-5.4 nano is available from OpenAI. Muse Spark 1.3 is available from Meta Model API.
GPT-5.4 nano
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.4 nano and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.4 nano vs Muse Spark 1.3.