GPT-5.4 nano or Muse Spark 1.3: which to choose?

What are we comparing?

This comparison pits two budget models, built for high volumes at a low price against each other: GPT-5.4 nano and Muse Spark 1.3, one from OpenAI, the other from Meta. The first dates from March 17, 2026, the second from September 2, 2026.

All figures below come from public sources checked on October 22, 2026: models.dev and OpenRouter for prices and capabilities, Epoch AI for scores.

Performance

On our capability index, GPT-5.4 nano scores 71.7 out of 100 and Muse Spark 1.3 82.7. Muse Spark 1.3 leads by 11 points.

On the 2 benchmarks reported for both, GPT-5.4 nano wins 0 times and Muse Spark 1.3 2:

• OTIS Mock AIME (competition mathematics problems): GPT-5.4 nano 87.8%, Muse Spark 1.3 99.2%
• FrontierMath (very hard research-level mathematics): GPT-5.4 nano 44.9%, Muse Spark 1.3 74.4%

Which one costs less?

GPT-5.4 nano costs $0.20 per million input tokens and $1.25 per million output tokens; Muse Spark 1.3 costs $0.10 and $0.20.

For a typical agent task (read 20,000 tokens, write 2,000), expect $0.007 with GPT-5.4 nano versus $0.002 with Muse Spark 1.3. Muse Spark 1.3 is 2.7 times cheaper, a gap that adds up quickly over 1,000 tasks: $4.1 difference.

Run the numbers with your own volumes in the agent cost calculator.

Context and capabilities

Muse Spark 1.3 reads more in one go: 1,048,576 tokens of context (roughly 1,573 pages), versus 400,000 for GPT-5.4 nano.

Reasoning mode: GPT-5.4 nano yes, Muse Spark 1.3 yes. Tool calling: GPT-5.4 nano yes, Muse Spark 1.3 yes. Image input: GPT-5.4 nano yes, Muse Spark 1.3 yes.

Neither publishes its weights: both are used through an API.

In short

Our reading of the data:

• Choose Muse Spark 1.3 for a higher capability index, a lower cost, a larger context window and a more recent release.

This verdict relies on public figures; it does not replace a trial on your own tasks.