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Data

Data as of November 9, 2026 · How the score is built

CurrentProprietaryReasoning

Released Nov 9, 20261M contextMeta: Muse Ember model page

Muse Ember

Decision readingMuse Ember scores 56.2 out of 100 and ranks #64 of 214. This profile shows 4 source-displayable benchmark rows. API pricing is $0.1 input and $0.5 output per million tokens, with cached input at $0.004.

Released Nov 9, 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

56.2/100

field median 51.1#64 of 214 ranked models

Public

#64of 214

Verified —

Price

$0.10input / $0.50 output

input median $0.60cached $0.004 · blended $0.30

Speed

Not measured

field median 92 tok/sTime to first token not measured

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Published rows are visible, but no category has enough eligible evidence for a comparative rank.

Validate before choosing

4 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.

Source-linked · 4 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 scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%3 benchmarksVerified
Score pending
CodingWeight 20%0 benchmarksNot measured
Not measured
ReasoningWeight 17%0 benchmarksNot measured
Not measured
MultimodalWeight 12%1 benchmarkVerified
Score pending
KnowledgeWeight 12%0 benchmarksNot measured
Not measured
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathWeight 5%0 benchmarksNot measured
Not measured

4 of 848 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

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.

  1. Agentic3/3 verified
  2. CodingNot measured
  3. ReasoningNot measured
  4. Multimodal1/1 verified
  5. KnowledgeNot measured
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. MathNot measured
Verified sourceProvisionalNot measured

Benchmark ledger

Agentic 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.

Agentic3 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 4.0Score40.90%Versus best verified row

Best verified: Claude Sonnet 5.5 · 70.60%

Gap29.7 behindWeightDisplay only
OSWorld 2.1OSWorld 2.1 (all 108 tasks)Score69.5%Versus best verified row

Best verified: Claude Opus 5.5 · 81.8%

Gap12.3 behindWeightDisplay only
Agents' Last Exam (Linux)Agents' Last Exam, Linux subsetScore61.6%Versus best verified row

Best verified: Muse Ember · 61.6%

GapBest verifiedWeightDisplay only
Multimodal1 row
Multimodal benchmark values, best verified comparison, weight, and source status
PerceptionBench (tools)PerceptionBench with toolsScore80.6%Versus best verified row

Best verified: Muse Ember · 80.6%

GapBest verifiedWeightDisplay only

Bars run 0–100; the dark tick marks the best source-verified value

All 4 rows

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.

Current modelExplore all models

Muse Ember · 56.2 score · $0.30 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierMuse Ember

Horizontal: blended price per million tokens, log scale · Vertical: public score

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.

  1. Nov 9, 2026 · you are here

    Muse Ember

    Score 56.2 · $0.1 / $0.5

Base entry

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-ember-1.0Meta: Muse Ember models and pricing
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 from November 9, 2026 on the Meta Model API as muse-ember-1.0 (Responses API supported) and in Muse Code. Meta lists $0.10 input, $0.004 cached input and $0.50 output per million tokens up to 200K tokens of context, and $0.30 input, $0.012 cached input and $1.50 output above 200K. 1M-token context window, up to 512K output tokens. Input: text, images, audio and video. Meta does not publish weights.
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.004 per million cached input tokensMeta: Muse Ember models and pricing
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.

Muse Ember ranks #64 of 214 on the public leaderboard with a score of 56.24/100. It does not yet have enough sourced coverage for a verified position.

Muse Ember 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 from November 9, 2026 on the Meta Model API as muse-ember-1.0 (Responses API supported) and in Muse Code. Meta lists $0.10 input, $0.004 cached input and $0.50 output per million tokens up to 200K tokens of context, and $0.30 input, $0.012 cached input and $1.50 output above 200K. 1M-token context window, up to 512K output tokens. Input: text, images, audio and video. Meta does not publish weights.

4 of 848 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Last updated November 9, 2026. Runtime fields remain blank until a sourced snapshot exists.

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Questions

How does Muse Ember perform overall in AI benchmarks?

Muse Ember ranks #64 out of 214 models on the public BenchAlign leaderboard, with a score of 56.24/100. Its evidence status is Estimated, and this profile shows 4 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Muse Ember good for agentic tool use and computer tasks?

Muse Ember 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 Ember good for multimodal and grounded tasks?

Muse Ember has source-displayable benchmark coverage for multimodal and grounded 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.

Does Muse Ember have full benchmark coverage on BenchLM?

No. Muse Ember currently has 14 source-displayable rows. 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 Ember?

Muse Ember 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.

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Compare Muse Ember with every tracked model1019 comparisons