For most workflows, Muse Spark 1.3 is the stronger default — muse spark with better tool calling and first-try accuracy, same price.
The safest Muse Spark 1.3 vs Muse Spark default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Muse Spark 1.3 is the strongest answer here for Muse Spark 1.3 vs Muse Spark — pick it when quality of output matters more than the $1.25/1M/1M input you pay for it.
Claude Sonnet 5.5 is the cheaper way in for Muse Spark 1.3 vs Muse Spark, at $2.00/1M/1M input against Muse Spark 1.3's $1.25/1M/1M.
Muse Spark is the fastest of these for Muse Spark 1.3 vs Muse Spark — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Muse Spark 1.3 leads on coding with a score of 89 vs 89 for Muse Spark.
Both models are similarly priced — the decision comes down to capability, not cost.
Muse Spark 1.3 is the stronger default for coding tasks.
Muse Spark 1.3 is the safer default: it is built for coding agents and multimodal workflows that need few turns and clean output, which covers most of what people bring to this comparison.
Muse Spark earns its place when your work is mostly agentic tool-use and multimodal reasoning at aggressive pricing, even though it loses the overall count here.
Both models serve different primary workflows — Muse Spark 1.3 for coding agents and multimodal workflows that need few turns and clean output, Muse Spark for agentic tool-use and multimodal reasoning at aggressive pricing — so running each where it has a clear edge often beats forcing one to do both.
Switch the scoring lens to see whether the Muse Spark 1.3 vs Muse Spark answer changes when cost, speed, or long-document depth leads the decision.
Meta / Balanced / Aug 6, 2026
Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need frontier-ceiling reasoning or a mature developer ecosystem — Opus 5 and GPT-5.6 lead both.
Where the Muse Spark 1.3 vs Muse Spark recommendation shifts once you weigh price or latency differently.
Muse Spark with better tool calling and first-try accuracy, same price.
Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Muse Spark 1.3Meta | $1.25/1M | $4.25/1M | $21 | 1.0M tokens | Balanced | 89 | 84 | 85 |
| Muse SparkMeta | $1.25/1M | $4.25/1M | $21 | 1.0M tokens | Balanced | 89 | 88 | 90 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for Muse Spark 1.3 vs Muse Spark, what it is genuinely good at, and where we would steer you away from it.
The default answer for Muse Spark 1.3 vs Muse Spark — 89/100 on the coding axis, and the model we would start with unless the price below rules it out.
Meta's September 2, 2026 update to Muse Spark — a multimodal reasoning model for long-horizon agent and coding work, with a 1M context and native understanding of video, images and documents.
You need published benchmark evidence before choosing a model.
A point release of Muse Spark at the same price. Use it in place of the original Muse Spark; we cannot rank it against Claude or GPT models until comparable benchmark figures are published.
Full pricing, benchmark table and release notes on the Muse Spark 1.3 page.
Here for latency: it answers fastest of anything listed for Muse Spark 1.3 vs Muse Spark, at 89/100 on coding.
Meta Superintelligence Labs' first closed frontier model — a natively multimodal agentic reasoner (text, image, video, audio, PDF in) with a parallel-agent 'Contemplating mode', priced aggressively below rivals.
You need frontier-ceiling reasoning or a mature developer ecosystem — Opus 5 and GPT-5.6 lead both.
Superseded: Muse Spark 1.3 (September 2, 2026) is the current version at the same price. Meta's surprise pivot to closed frontier models is a genuine value play: GPT-5.5-tier intelligence with the broadest multimodal input support, at prices that undercut OpenAI and Anthropic. The young API ecosystem is the main practical drawback.
Full pricing, benchmark table and release notes on the Muse Spark page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Muse Spark 1.3 wins on more of the categories we score — coding, research, reasoning — so it is the better default of the two. Muse Spark is the better pick when your work is mostly agentic tool-use and multimodal reasoning at aggressive pricing. Neither is universally "better": Muse Spark 1.3 is aimed at coding agents and multimodal workflows that need few turns and clean output, Muse Spark at agentic tool-use and multimodal reasoning at aggressive pricing.
Both models are similarly priced at $1.25/1M input tokens. The decision should come down to capability, not cost.
Both Muse Spark 1.3 and Muse Spark have the same 1.048576M context window.
Muse Spark 1.3 and Muse Spark are similarly matched on coding. Claude Opus 5.5 is the overall coding leader in this directory at 100/100.
Both Muse Spark 1.3 and Muse Spark have similar speed profiles — rated balanced. Neither will be the bottleneck if latency is your deciding factor.
Meta published no standard benchmark table we could verify for this update. Free in the Meta AI app, but API access runs through third-party hosts. Avoid it if you need published benchmark evidence before choosing a model. That is the main case for looking at Muse Spark instead.
Trails the frontier on raw intelligence: AA Intelligence Index 54 vs Claude Opus 5 (61) and GPT-5.6 Sol (59). Weak on some hard agentic evals (27% tau3-Banking) and the API ecosystem is young — public API only since July 2026. Avoid it if you need frontier-ceiling reasoning or a mature developer ecosystem — Opus 5 and GPT-5.6 lead both. Against Muse Spark 1.3 specifically, the two are close enough on capability that price and speed decide it.
Take a moderate workload of 10M input and 2M output tokens a month. Muse Spark 1.3 runs $21.00 (at $1.25/1M in and $4.25/1M out); Muse Spark runs $21.00 (at $1.25/1M in and $4.25/1M out). The gap is small enough that price should not decide this one. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is Muse Spark 1.3 for coding agents and multimodal workflows that need few turns and clean output, with Muse Spark handling agentic tool-use and multimodal reasoning at aggressive pricing. Since Muse Spark 1.3 is both the stronger and the cheaper option here, a split mainly makes sense if Muse Spark covers a capability you specifically need.