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Muse Spark 1.3

Muse Spark 1.3 is a Meta model with 1.05M context, $1.25 in / $4.25 out per million tokens, last verified October 2, 2026. Open weights: no. Public-board scores are linked to the publisher; vendor-only figures stay in the watch-out, not on the board.

Muse Spark 1.3 is Meta's September 2026 frontier refresh with a 1M-token context for coding and agent workflows.

Recorded profile verification October 2, 2026Individual provider fields may change

AI model specification details
SpecificationMuse Spark 1.3
ProviderMeta
TierFrontier
Context window1.05M
Max outputNot verifiedUnverified
Input / 1M tokens$1.25
Output / 1M tokens$4.25
WeightsClosed
ParametersNot verifiedUnverified
Reasoning levelsminimal, low, medium, high, xhigh, max
Modalitiestext, image, video, audio, pdf
API model idmuse-spark-1.3
ReleasedSeptember 2, 2026

Pricing tiers: Meta Standard $1.25/$4.25 per MTok, cached $0.15; prompts/completions are not used for training. Contributor uses a distinct SKU at $0.10/$0.20, cached $0.002, and permits training on prompts/completions. No long-context premium. Search grounding adds $2.50 per 1,000 queries.

Publisher evidence

Published benchmark results

Each result keeps its source date visible. Dates refer to source publication or capture unless the source explicitly states when it measured the result. A missing benchmark is not treated as a zero.

Published benchmark results for Muse Spark 1.3
BenchmarkScoreSource dateSource
Artificial Analysis Intelligence Index [max]Muse Spark 1.3 (max)482026-10-01Artificial Analysis · View source
DeepSWE 1.1Meta max / mini-swe-agent; vendor chart 75.4 versus Spark 1.2 xhigh 55.0; source publication September 2, experiment date unverified; separate from Datacurve xhigh rowCross-model comparability not verified75.4%2026-09-02Meta launch table · View source

Best for

  • Long-horizon coding agents
  • Frontier quality below frontier pricing
  • Meta ecosystem

Watch out

Max effort is Standard Spark 1.3 only; Contributor and Spark 1.2 lack it. None returns HTTP 400; omitted effort is model-determined. Reasoning counts toward output budget and billing. Spark 1.3 audio may degrade; Meta directs audio work to 1.2 or Voice Transcribe. Standard 3,000 RPM/4M TPM versus Contributor 100 RPM/3M TPM quotas apply per team. Exact output cap and parameter count remain unknown. Meta's 75.4% DeepSWE max/mini-swe-agent report is separate from independent xhigh observations.

History

Muse Spark 1.3 timeline

Release and status events for this model that passed two-source verification — dated, sourced, and linked.

Source receipts

Catalog figures for this model were checked against the following sources.

Common questions

Muse Spark 1.3

Answered from the verified figures on this page rather than general guidance.

How much does Muse Spark 1.3 cost per million tokens?
Muse Spark 1.3 lists base rates of $1.25 per million input tokens and $4.25 per million output tokens. Estimate both input and output token volume and any additional charges for your workload. Meta Standard $1.25/$4.25 per MTok, cached $0.15; prompts/completions are not used for training. Contributor uses a distinct SKU at $0.10/$0.20, cached $0.002, and permits training on prompts/completions. No long-context premium. Search grounding adds $2.50 per 1,000 queries.
What is Muse Spark 1.3's context window?
Muse Spark 1.3 accepts about 1.05M tokens of context. That only matters if you routinely send very long documents, large codebases, or multi-turn histories that approach that limit.
What is Muse Spark 1.3 best for?
Muse Spark 1.3 is a frontier tier from Meta. It suits long-horizon coding agents, frontier quality below frontier pricing, meta ecosystem. Max effort is Standard Spark 1.3 only; Contributor and Spark 1.2 lack it. None returns HTTP 400; omitted effort is model-determined. Reasoning counts toward output budget and billing. Spark 1.3 audio may degrade; Meta directs audio work to 1.2 or Voice Transcribe. Standard 3,000 RPM/4M TPM versus Contributor 100 RPM/3M TPM quotas apply per team. Exact output cap and parameter count remain unknown. Meta's 75.4% DeepSWE max/mini-swe-agent report is separate from independent xhigh observations.
Model comparison catalogBenchmark library