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ModelCap

Muse Spark 1.3

Arena #10No linked weights

Meta·#6 of 351 on the current board·cheaper than #4 Muse Wonder

Muse Spark 1.3 is a language model from Meta. It ranks #6 of 351 on ModelCap's current board, with an Index score of 83.4, measured on 3 public benchmarks. Its score range of 78.6–88.2 spans positions #1–#19. It is listed at $1.25 per million input tokens and $4.25 per million output tokens from one provider. It reads up to 1M tokens of context, with no downloadable weights linked in the current source data.

Figures as of 18 Oct 2026, 00:40 UTC · download the public dataset · methodology

ModelCap Index · Current board
83.4#6
Measured on 3 public benchmarks · range 78.6–88.2
Evidence as of 16 Oct 2026, 00:00 UTC
Market Gravity
37.2
Secondary market signal
Input
$1.25
per 1M tokens
Output
$4.25
per 1M tokens
Context
1M
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Meta$1.25$4.251M—100.0%

Reasoning efforts

Best supported result can inform ModelCap

Published Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.

EffortAgent scoreSource rankSampleSource
Max
Muse Spark 1.3 (Max)
3.82%
CI 3.0–4.7%
#147.4M obs
74K sessions
LMArena Agent
Match 100%

Related community configurations

Human preference rating
ConfigurationRatingSource rankVotesSource
Max
Muse Spark 1.3 (Max)
1494
CI 1489–1500
#1018KLMArena
Match 100%

Other versions (2)

ModelCap Index · Current board

Methodology
83.4
Measured on 3 public benchmarks
Current board
#6 of 351
Score range
78.6–88.2
Rank range
#1–#19
Evidence as of
16 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall, LMArena Agent
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 3 public benchmark observations across 3 boards
Index support
65.5% · strong
Identity binding
Exact catalogue product · meta/meta/muse-spark-1.3 · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
3
Qualified Index evidence point
83.4
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
83.4
Evidence status
confirmed · 88% mass
General preference
84.8
Coding
82.2
Agents & tools
62.5
Reasoning
—
Evidence breadth
97%
Evidence coverage
66%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
30.7
Liquidity (providers × uptime)
34.5
Open reach (HF downloads)
—
Surface (context / tools / modalities)
100.0
Freshness
84.2
  • · OpenRouter popularity #57
  • · 1 live provider
  • · Catalogue: context 1048576, reasoning, tools, modalities Text/Image/Video/File
  • · First seen 2026-09-02

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
45.3
partial · 56% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
80.0
Evaluation provenance
76.2

Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
37.2
OpenRouter weekly popularity
#57 of 341

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#10 of 416
Rating
1494.4
95% confidence interval
1489–1500
Votes
18K
Source published at
15 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
30.7

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
34.5

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
84.2

Time since first public availability, on a six-month half-life.

Specification

Model ID
meta/muse-spark-1.3
Context window
1M tokens
Declared output cap
944K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text, Image, Video, File
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.15 / 1M
First seen on OpenRouter
2 Sept 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Supported: Moderated

Compare Muse Spark 1.3 with

Pick any model

Benchmark leaderboards featuring Muse Spark 1.3

All leaderboards
Public benchmark boards on which Muse Spark 1.3 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14941489–1500#10 of 416Max15 Oct 2026
Arena coding leaderboardArena (LMArena)15351526–1544#15 of 411Max15 Oct 2026
LMArena Agent leaderboardLMArena3.8%3.0%–4.7%#14 of 52Max16 Oct 2026
Artificial Analysis Intelligence IndexArtificial Analysis48.1#21 of 134Max7 Oct 2026
Terminal-Bench 2.1 (Artificial Analysis run)Artificial Analysis84.3%#17 of 128Max1 Oct 2026
Humanity's Last Exam (Artificial Analysis run)Artificial Analysis48.7%#25 of 267Max30 Sept 2026
Terminal-Bench 4.0 leaderboardTerminal-Bench (Laude Institute)14.6%11.6%–17.5%#32 of 35Muse Code · X-High2 Sept 2026

Alternatives to Muse Spark 1.3, by the numbers

Ranked neighbours

Models within 3 places of #6 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked Meta models

The same publisher's other current models with a public Index position.

Muse Spark 1.3: common questions

How does Muse Spark 1.3 rank among AI models?

Muse Spark 1.3 holds ModelCap Index position #6 of 351 ranked language models as of 18 October 2026, with an Index score of 83.4 (interval 78.6–88.2); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Muse Spark 1.3 cost per 1M tokens?

Muse Spark 1.3 is listed at $1.25 per 1M input tokens and $4.25 per 1M output tokens as of 18 October 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $4.63 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Muse Spark 1.3?

Muse Spark 1.3 has a published context window of 1M tokens (1,048,576). The snapshot lists a 943,718 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Muse Spark 1.3 open-weight?

No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.

Which API providers serve Muse Spark 1.3?

One provider serves Muse Spark 1.3 through OpenRouter as of 18 October 2026: Meta. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Muse Spark 1.3 been evaluated on?

Muse Spark 1.3 has published results on 7 public boards tracked by ModelCap as of 18 October 2026: Arena text 1494 (#10 of 416), Arena coding 1535 (#15 of 411), LMArena Agent 3.8% (#14 of 52), AA Intelligence Index 48.1 (#21 of 134) and AA Terminal-Bench 2.1 84.3% (#17 of 128) and more. Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

How does Muse Spark 1.3 compare with Gemini 3.8 Flash?

Muse Spark 1.3 ranks #6 (Index 83.4) and Gemini 3.8 Flash ranks #5 (Index 83.5) on the ModelCap Index as of 18 October 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was Muse Spark 1.3 released?

Muse Spark 1.3 first appeared in the catalogue on 2 Sept 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.