Today's price · per 1M tokens
Input
$1.25
per 1M tokens
Output
$4.25
per 1M tokens
Blended
$2.00
blended $/1M — 3:1 weighted input:output
Cached input
$0.150
12% of input — prompt caching
How this price is scoped: Meta Model API standard-tier list price, per 1M tokens, with no long-context premium — the tier on which Meta states prompts and completions are not used for training. A cheaper contributor tier ($0.10 input / $0.20 output per 1M) trades training rights and a far lower rate limit (100 vs 3,000 requests/min) for the discount, so it is not the tracked list price. Search grounding is billed separately per 1,000 queries and is not included in the token rate.
Price receipt
We read Meta's own pricing page on and found muse-spark-1.2 listed with a price on the same tier — that read is where the number above comes from. We keep the page text we read; its content hash is ebbc499616.
Overview
The previous Muse Spark version on the Meta Model API, superseded by Muse Spark 1.3 on 2026-09-02 but still sold at the same rate — a multimodal agentic model with a 1M-token context that takes text, image, video, audio and PDF input, retrained for coding, whole-repository work and computer use. $1.25/$4.25 per 1M tokens, with cached input at $0.15 — the same list price as Muse Spark 1.1 and 1.3. Like 1.1 it is API-only: there are no open weights. Meta still recommends 1.2 over 1.3 for audio input, where 1.3's support is not yet complete.
Capabilities
struck through = not supportedBenchmark performance
accuracy % · higher is better- AA Intelligence Index: 39.6 (Artificial Analysis composite across reasoning, knowledge and coding evals)
- AA-Omniscience Index: 27.2 (−100–100)
- GDPval-AA v2: 1615 ELO (Real-world work tasks, human baseline = 1000)
- LMSYS Chatbot Arena: 1499.6 ELO (Human preference)
- Ranks #45 of 100 benchmarked models by average score
- Ranks #29 of 195 comparably-measured models by percentile score, across 7 independent measurements
- Ranks #77 of 195 comparably-tested models by normalized performance per dollar
- Strongest at SWE-Bench Verified — 86.6%, #14 of 40
Source: Artificial Analysis, Vals AI (SWE-bench Verified, xhigh effort), LMSYS Chatbot Arena (UC Berkeley) · updated · See full rankings →
Specifications
- Provider
- Meta
- Context window
- 1M tokens
- Modality
- text, image, video, audio
- Parameters
- Proprietary
- Open source
- No — proprietary
- Released
- Status
- Current
- Last updated
- Tags
Availability verified: — listed on Meta's own page