Capability
60.3/100
field median 57.5
#49 of 216 ranked models
Model profile · Meta
Muse Spark 1.2
Released Aug 5, 2026 — see all recent releases
Muse Spark 1.2 scores 60.3 out of 100 and ranks #49 of 216. This profile shows 3 source-displayable benchmark rows; its strongest eligible category is Agentic at #20. API pricing is $1.25 input and $4.25 output per million tokens, with cached input at $0.15.
Data as of August 5, 2026 · How the score is built
Strongest published evidence
Agentic ranks #20. Particularly useful for coding agents, browser research, and computer-use workflows.
Validate before choosing
3 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
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.
Price
$1.25input / $4.25 output
input median $1
cached $0.15 · blended $2.75
Speed
Not measured
field median 89 tok/s
Time to first token not measured
Context
1Mtokens
field median 201,500
Maximum output length is tracked separately
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Muse Spark 1.2 category percentile values
- Agentic85th percentile
- Coding80th percentile
- ReasoningNot eligible
- KnowledgeNot eligible
- MathNot eligible
- MultilingualNot eligible
- MultimodalNot eligible
- Instruction followingNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#20/132
- Coding#27/132
- ReasoningNot ranked
- KnowledgeNot ranked
- MathNot ranked
- MultilingualNot ranked
- MultimodalNot ranked
- Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Current modelMuse Spark 1.2 · 60.3 score · $2.75 blended per million tokens
Horizontal: blended price per million tokens, log scale · Vertical: public score
How 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.
- Agentic1/1 verified
- Coding2/2 verified
- ReasoningNot measured
- KnowledgeNot measured
- MathNot measured
- MultilingualNot measured
- MultimodalNot measured
- Inst. FollowingNot measured
Verified sourceProvisionalNot measured
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-1.2Meta: Muse Spark 1.2 model page
- Context window
- 1MMeta: Muse Spark 1.2 model page
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not disclosed by the provider
- Availability
- Available through Meta Model API as muse-spark-1.2. Meta also offers a lower-priced muse-spark-1.2-contributor SKU whose data may be used to improve Meta products.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.15 per million cached input tokensMeta: Muse Spark 1.2 model page
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
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 #20 of 132Percentile 85thWeight 22%1 benchmarkVerified | 57.2 | #20 of 132 | 85th | 22% | 1 benchmark | Verified |
| CodingRank #27 of 132Percentile 80thWeight 20%2 benchmarksVerified | 58.7 | #27 of 132 | 80th | 20% | 2 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
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.
Coding2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score82.9% | Versus best verified row Best verified: Qwen3.8 Max · 86.6% | Gap3.7 behind | WeightDisplay only | Provider exact |
| deepSwe | Score59.3% | Versus best verified row Best verified: GPT-5.6 Sol · 72.7% | Gap13.4 behind | WeightDisplay only | Provider exact |
Agentic1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score82.9% | Versus best verified row Best verified: Qwen3.8 Max · 86.6% | Gap3.7 behind | WeightDisplay only | Provider exact |
Lineage
The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Apr 8, 2026
Muse SparkScore 70.5 · Price not listed
Jul 9, 2026
Muse Spark 1.1Score 76.2 · Price not listed
Aug 5, 2026 · you are here
Muse Spark 1.2Score 60.3 · $1.25 / $4.25
1.2 · 1.2
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.
Muse Spark 1.2 ranks #49 of 216 on the public leaderboard with a score of 60.25/100. It does not yet have enough sourced coverage for a verified position.
Muse Spark 1.2 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 Meta Model API as muse-spark-1.2. Meta also offers a lower-priced muse-spark-1.2-contributor SKU whose data may be used to improve Meta products.
Muse Spark 1.2 sits in the Muse Spark family with Muse Spark 1.1, Muse Spark. Its explicit predecessor is Muse Spark 1.1. 3 of 381 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Agentic at #20, while its lowest eligible position is Coding at #27. particularly useful for coding agents, browser research, and computer-use workflows.
Radar
Full release historyMuse Spark 1.2 release history
Muse Spark 1.2 released
Meta · Model release
Source confirmed
Frequently asked questions
How does Muse Spark 1.2 perform overall in AI benchmarks?
Muse Spark 1.2 ranks #49 out of 216 models on the public BenchAlign leaderboard, with a score of 60.25/100. Its evidence status is Estimated, and this profile shows 3 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Muse Spark 1.2 good for coding and programming?
Muse Spark 1.2 ranks #27 out of 132 eligible models for coding and programming, with a public category score of 58.7/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Muse Spark 1.2 good for agentic tool use and computer tasks?
Muse Spark 1.2 ranks #20 out of 132 eligible models for agentic tool use and computer tasks, with a public category score of 57.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Which sibling models are related to Muse Spark 1.2?
Muse Spark 1.2 belongs to the Muse Spark family. Related tracked variants include Muse Spark 1.1, Muse Spark. 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 1.2 have full benchmark coverage on BenchLM?
No. Muse Spark 1.2 currently has 4 source-displayable rows across 381 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 1.2?
Muse Spark 1.2 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.
Last updated August 5, 2026. Runtime fields remain blank until a sourced snapshot exists.
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