meta
Meta: Muse Spark 1.2
meta/muse-spark-1.2
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to OpenRouter's catalog, meta/muse-spark-1.2 is a Meta reasoning model intended for complex agentic tasks. It accepts text, images, video, and files, including PDFs, and returns text within a 1M-token context window. The catalog reports mandatory reasoning with configurable effort, tool and structured-output parameters, and benchmark entries across agentic and design arenas. An independent model card was not available in this source pack, so real-world suitability should be validated on the intended workload.[1]
Strengths
- The catalog describes broad multimodal input support spanning text, images, video, and files, including PDF documents, with text output.[1]
- A 1M-token context window, mandatory reasoning with multiple effort settings, and support for tools and structured outputs may suit complex, tool-using workflows.[1]
Limitations
- The only supplied evidence is an OpenRouter catalog entry; an independent model card was not available, so capabilities and benchmark relevance require workload validation.[1]
- Output is limited to text despite the reported multimodal input support.[1]
- The listing does not provide a knowledge cutoff, Hugging Face identifier, expiration date, license terms, hardware requirements, or safety guarantees.[1]
Where to use it
Sources
- [1] OpenRouter catalog · Meta: Muse Spark 1.2Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, and PDF documents, returns text, and offers a 1M-token context window....
Specifications
- Model ID
- meta/muse-spark-1.2
- Canonical ID
- meta/muse-spark-1.2-20260805
- Creator
- meta
- Added to OpenRouter
- 05.08.2026
- Context length
- 1,048,576
- Modality
- text+image+file+video->text
- Input modalities
- text, image, video, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $1.25 / out $4.25
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: mandatory · default medium · efforts: xhigh, high, medium, low, minimal · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | AA — next 20% of the cohort | — |
| Agents | AA — next 20% of the cohort | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default medium · efforts: xhigh, high, medium, low, minimal · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | input: video |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Coding index | 72.2 | AA — next 20% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 43.2 | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · agenticgamedevwin rate 43% · rank 15 | 1,126Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · androidnativewin rate 52.6% · rank 13 | 1,210Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · blender3dwin rate 42.9% · rank 16 | 1,053Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · codetovideowin rate 39.8% · rank 20 | 1,102Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · fullstackwin rate 47.4% · rank 18 | 1,188Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · htmlslideswin rate 40% · rank 22 | 1,031Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 47.4% · rank 25 | 1,176Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · pdfwin rate 40.4% · rank 28 | 1,118Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · python-pptxslideswin rate 48.2% · rank 19 | 1,154Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · spreadsheetwin rate 46.1% · rank 25 | 1,092Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · webappswin rate 49.8% · rank 20 | 1,204Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 51.8% · rank 22 | 1,286Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · asciiartwin rate 54.8% · rank 7 | 1,278Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 52.4% · rank 14 | 1,307Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 57.3% · rank 8 | 1,330Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 50.5% · rank 20 | 1,295Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 54.4% · rank 14 | 1,274Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 52.4% · rank 18 | 1,301Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 52.6% · rank 11 | 1,310Elo | SS — top 10% of the cohort | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Meta | 1,048,576 | $1.25 | $4.25 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.