Data as of October 17, 2026 · How the score is built
Released Sep 2, 20261M contextMeta: Muse Spark 1.3 model page
Muse Spark 1.3
Decision readingMuse Spark 1.3 is tracked, but not publicly ranked yet. The profile exposes 20 sourced benchmark rows and leaves unsupported fields blank until a published record exists.
Released Sep 2, 2026 — see all recent releases
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
Unranked
field median 49.6Not eligible for a public rank
Price
$1.25input / $4.25 output
input median $0.75cached $0.15 · blended $2.75
Speed
128tok/s
field median 92 tok/sFirst token 71.21 s
Context
1Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Reasoning ranks #6. Particularly strong for complex reasoning, multi-step problem solving, and analytical tasks.
Validate before choosing
20 published rows leave some tracked benchmark slots empty.
Source-linked · 20 displayable benchmark rows
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank Not rankedWeight 22%9 benchmarksVerified | 75.3 | 9 benchmarks | Verified | |||
| CodingRank Not rankedWeight 20%6 benchmarksVerified | 68.7 | 6 benchmarks | Verified | |||
| ReasoningRank #6 of 28Percentile 81stWeight 17%2 benchmarksVerified | 82.9 | 2 benchmarks | Verified | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| MathRank Not rankedWeight 5%2 benchmarksVerified | 78.5 | 2 benchmarks | Verified |
20 of 681 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic9/9 verified
- Coding6/6 verified
- Reasoning2/2 verified
- MultimodalNot measured
- KnowledgeNot measured
- MultilingualNot measured
- Inst. Following1/1 verified
- Math2/2 verified
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding6 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierSWE v2 | Score25.8% | Versus best verified row Best verified: GPT-6 Astra · 65.5% | Gap39.7 behind | Weight8% ref. weight | Benchmark exact |
| DeepSWE | Score75.4% | Versus best verified row Best verified: Muse Wonder Full · 79.0% | Gap3.6 behind | WeightDisplay only | Provider exact |
| Terminal-Bench 2.1 | Score88.8% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap4 behind | WeightDisplay only | Provider exact |
| SWE-Atlas Codebase QnA | Score59.4% | Versus best verified row Best verified: Ling 3.1 Flash · 64.5% | Gap5.1 behind | WeightDisplay only | Provider exact |
| CursorBench 4.0 | Score41.6% | Versus best verified row Best verified: Claude Opus 5.5 · 57.8% | Gap16.2 behind | WeightDisplay only | Benchmark exact |
| Bug Hunt Bench | Score32.2 fixes | Versus best verified row Best verified: Claude Sonnet 5.5 · 51.3 fixes | Gap19.1 behind | WeightDisplay only | Benchmark exact |
Agentic9 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI run | Score72.3% | Versus best verified row Best verified: GPT-6 Astra · 87.3% | Gap15 behind | Weight4% ref. weight | |
| Terminal-Bench 2.1 | Score88.8% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap4 behind | WeightDisplay only | Provider exact |
| JobBench | Score64.9% | Versus best verified row Best verified: Muse Wonder Full · 75.3% | Gap10.4 behind | WeightDisplay only | Provider exact |
| AutomationBench | Score49.4% | Versus best verified row Best verified: DeepSeek V4.1 Flash 1017 · 60.5% | Gap11.1 behind | WeightDisplay only | Provider exact |
| DeepSearchQA | Score89.4% | Versus best verified row Best verified: Atria Dawn Preview · 96.0% | Gap6.6 behind | WeightDisplay only | Provider exact |
| OSWorld 2.0 | Score66.9% | Versus best verified row Best verified: GPT-6 Astra · 72.6% | Gap5.7 behind | WeightDisplay only | Provider exact |
| ApprenticeBenchApprenticeBench: end-to-end computer use, continual learning, and long-horizon agency on a real accounts-payable job | Score19% | Versus best verified row Best verified: Claude Fable 5.1 · 72% | Gap53 behind | WeightDisplay only | Benchmark exact |
| CWE-bench v1 | Score55.0% | Versus best verified row Best verified: GPT-6 Astra · 68.0% | Gap13 behind | WeightDisplay only | Benchmark exact |
| MazeBenchMazeBench: visual spatial reasoning in a 3D open world | Score0% | Versus best verified row Best verified: GPT-6 Astra · 23% | Gap23 behind | WeightDisplay only | Benchmark exact |
Reasoning2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MRCR v2 256K-512KOpenAI MRCR v2 8-needle 256K-512K | Score98.5% | Versus best verified row Best verified: GPT-6 Astra · 100.0% | Gap1.5 behind | WeightDisplay only | Provider exact |
| MRCR v2 512K-1MOpenAI MRCR v2 8-needle 512K-1M | Score98.1% | Versus best verified row Best verified: Muse Spark 1.3 · 98.1% | GapBest verified | WeightDisplay only | Provider exact |
Inst. Following1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Gray Swan IPI (15 attempts)Gray Swan Indirect Prompt Injection, attack success at 15 attempts | Score15.9% | Versus best verified row Best verified: Gemini 4 Argon · 0.7% | Gap15.2 behind | WeightDisplay only | Provider exact |
Math2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | Score74.035% | Versus best verified row Best verified: GPT-6 Astra · 93.684% | Gap19.6 behind | WeightWeighted 30% | Benchmark exact |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | Score46.341% | Versus best verified row Best verified: GPT-6.1 Sol · 100.000% | Gap53.7 behind | WeightWeighted 10% | Benchmark exact |
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- muse-spark-1.3Meta Muse Spark 1.3 model page
- Context window
- 1MMeta Muse Spark 1.3 model page
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, image, video, documentMeta Muse Spark 1.3 model page
- Output modalities
- textMeta Muse Spark 1.3 model page
- Parameters
- Not disclosed by the provider
- Availability
- Meta Model API · Muse CodeMeta AI Research Muse Spark 1.3 launch
- Cloud regions
- Not tracked yet
- Lifecycle
- activeMeta AI Research Muse Spark 1.3 launch
- API capabilities
- OpenAI-compatible requests · tool calling · native image, video, and document perceptionMeta Muse Spark 1.3 model page
- Prompt caching
- Published at $0.15 per million cached input tokensMeta: Muse Spark 1.3 model page
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track Muse Spark 1.3, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.
Muse Spark 1.3 is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Available through Muse Code and Meta Model API as `muse-spark-1.3`. Meta also offers a lower-priced `muse-spark-1.3-contributor` SKU whose data may be used to improve Meta products. Previously available reasoning modes are live; Meta says max reasoning will follow additional safety testing.
Muse Spark 1.3 sits in the Muse Spark family with Muse Spark 1.1, Muse Spark, Muse Spark 1.2. Its explicit predecessor is Muse Spark 1.2. 20 of 681 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Reasoning at #6. particularly strong for complex reasoning, multi-step problem solving, and analytical tasks.
Last updated October 17, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Muse Spark 1.3 perform overall in AI benchmarks?
Muse Spark 1.3 has 20 source-displayable benchmark rows, but it does not qualify for a public overall rank. The available rows remain visible by category without being converted into a site-wide score. Missing evidence stays blank instead of being estimated from an earlier model.
Is Muse Spark 1.3 good for coding and programming?
Muse Spark 1.3 has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Muse Spark 1.3 good for mathematics?
Muse Spark 1.3 has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Muse Spark 1.3 good for reasoning and logic?
Muse Spark 1.3 ranks #6 out of 28 eligible models for reasoning and logic, with a public category score of 82.9/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Muse Spark 1.3 good for agentic tool use and computer tasks?
Muse Spark 1.3 has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Muse Spark 1.3 good for instruction following?
Muse Spark 1.3 has source-displayable benchmark coverage for instruction following, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Which sibling models are related to Muse Spark 1.3?
Muse Spark 1.3 belongs to the Muse Spark family. Related tracked variants include Muse Spark 1.1, Muse Spark, Muse Spark 1.2. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does Muse Spark 1.3 have full benchmark coverage on BenchLM?
No. Muse Spark 1.3 currently has 43 source-displayable rows across 681 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Muse Spark 1.3?
Muse Spark 1.3 has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.