Muse Spark 1.3

MetaKey muse-spark-1.3Also reported as meta/muse-spark-1.3, sk/muse-spark-1.3, nutaraline/muse-spark-1.3

Rank
#45
by active users
Active users
8
Down 2 from 10 active users in the previous 7 days. vs previous 7 days
Adoption
1.3%
of 610 accounts
Tokens
1.7B
cache included
Est. cost
$386
at public list prices
First seen
Sep 2, 2026
in any submission

Nov 6–12, 2026 (UTC)610 accounts100% of tokens from an identified modelData through Nov 12, 2026, 08:06 UTCHow we count

Daily active users

Distinct accounts that used this model on each UTC day.

0 active users on Nov 12, 2026

Daily active users for Muse Spark 1.3, Nov 6, 2026 to Nov 12, 2026. Peak 7. Use the left and right arrow keys to read each day.840
Show daily values
Daily active users and tokens for Muse Spark 1.3
Date (UTC)Active usersTokens
Nov 6, 2026135.4M
Nov 7, 20267515.2M
Nov 8, 20262711.9M
Nov 9, 20264279.8M
Nov 10, 20263145.3M
Nov 11, 2026119.8M
Nov 12, 202600

Token mix

How the 1.7B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input10%
  • Output0.1%
  • Cache read89%
  • Cache write0%
  • Reasoning0.2%

Agents that carry Muse Spark 1.3

Each agent's share of this model's tokens, and how many accounts used the model through it.

  1. Muse Code94% of this model's tokens5active users
  2. Pi4.7% of this model's tokens1active users
  3. Reasonix1.2% of this model's tokens1active users
  4. OpenCode<0.1% of this model's tokens1active users
  5. Oh My Pi<0.1% of this model's tokens1active users

Benchmarks

The best result for Muse Spark 1.3 in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark. Agent rows also show Tokscale usage through that agent, side by side with the score. Usage does not explain the score.

All benchmarks
  • Epoch Capabilities IndexOverall · Epoch AI
    158.2
    Rank #26 of 158 matched modelsNo conditions reportedModel released Sep 2, 2026Source: epoch.ai (opens in a new tab)
  • Terminal-Bench 4.1Agentic coding · Terminal-Bench
    14.8%
    Rank #20 of 23 matched modelsXHigh · Muse CodePublished Nov 3, 2026Source: tbench.ai (opens in a new tab)

    Tokscale usage: Muse Code carried 94% of Muse Spark 1.3 tokens in the last 7 days (5 active users).

  • CursorBenchAgentic coding · Cursor, collected by Epoch AI
    41.6%
    Rank #14 of 21 matched modelsMaxModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
    Show 5 more results with other run conditionsHide the other results
    • Listed as Muse Spark 1.3 Extra High
      37.5%
      XHighModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
    • Listed as Muse Spark 1.3 High
      33.4%
      HighModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
    • Listed as Muse Spark 1.3 Medium
      32.6%
      MediumModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
    • Listed as Muse Spark 1.3 Low
      29.3%
      LowModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
    • Listed as Muse Spark 1.3 Minimal
      24.3%
      MinimalModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
  • FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI
    25.8%
    Rank #15 of 23 matched modelsMax · proximusModel released Sep 2, 2026Source: frontierswe.com (opens in a new tab)
  • WebDev ArenaWeb development · LMArena
    1,659
    Rank #13 of 110 matched modelsMaxPublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
    Show 1 more result with other run conditionsHide the other results
    • Listed as Muse Spark 1.3 (xHigh)
      1,621
      XHighPublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • Agent ArenaAgents · LMArena
    +0.03
    Rank #15 of 48 matched modelsMax · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI
    74.4%
    Rank #26 of 90 matched modelsXHighRun date Sep 16, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 95.1%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.

    Show 1 more result with other run conditionsHide the other results
    • Listed as muse-spark-1.3_max
      74.0%
      MaxRun date Sep 18, 2026Source: epoch.ai (opens in a new tab)

Not evaluated: GPQA Diamond, Humanity's Last Exam, SimpleQA Verified, DeepSWE. A missing result is not a score of zero.

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. Meta is the lab's own API and the reference price for the estimates below.

Price at real agent usageEstimate at list prices

What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.

At this model's mix
$0.27
Est. per 1M tokens
89% cache reads
At the community mix
$0.20
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$2
Per 1M tokens at list prices
No cache

Cache reads were 89% of Muse Spark 1.3 tokens in the last 7 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.

Assumptions

  • Meta list prices per 1M tokens: input $1.25, output $4.25, cache read $0.15.
  • This model's mix is its own input, output, cache and reasoning tokens in the last 7 days.
  • The community mix is the tokens of every identified model in the last 7 days.
  • This is an estimate at list prices, not what anyone paid.
  • Reasoning tokens are priced as output.
  • Long-context tiers, batch pricing and discounts are not applied.
  • Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
  • No cache-write price is listed, so cache writes are priced as input.

List prices by provider

  • MetaReferencemuse-spark-1.3
    $1.25 input per 1M tokens$4.25 output per 1M tokens$0.15 cache read per 1M tokensCache write not listed1.05M tokens of context
  • OpenRoutermeta/muse-spark-1.3
    $1.25 input per 1M tokens$4.25 output per 1M tokens$0.15 cache read per 1M tokensCache write not listed1.05M tokens of context
  • Vercel AI Gatewaymeta/muse-spark-1.3
    $1.25 input per 1M tokens$4.25 output per 1M tokens$0.15 cache read per 1M tokensCache write not listed1.05M tokens of context

Specs

From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.

Context window
1.05M tokens
Max output
131K tokens
Input
Text, Image, Video, PDF, Audio
Output
Text
Knowledge cutoff
— not listed
Release date
Sep 2, 2026
Open weights
No
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used Muse Spark 1.3 most in this period, by tokens. Hidden accounts are never listed.

  1. 1Khaliq@khaliqgant1.5Btokens$313est. cost4active days$313 est. cost · 4 active days
  2. 2AllThatMagic@AllThatMagic79.7Mtokens—est. cost3active daysno price · 3 active days
  3. 3Yags@whyyagswhy68.9Mtokens$62est. cost3active days$62 est. cost · 3 active days
  4. 4Ziyang Fang@Fangziyang091040.8Mtokens$11est. cost4active days$11 est. cost · 4 active days
  5. 5taekun1@taekum1315Ktokens<$1est. cost1active days<$1 est. cost · 1 active days
  6. 6Alec Z@offcall162Ktokens<$1est. cost1active days<$1 est. cost · 1 active days
  7. 7Zenco@notzenco44.9Ktokens<$1est. cost1active days<$1 est. cost · 1 active days
  8. 8Brad Lishman@bradlishman44.7Ktokens—est. cost1active daysno price · 1 active days

More from Meta

Other Meta models in the same period, by active users.

  1. Muse Spark 1.3 Contributor2.3% adoption14active users
  2. Muse Wonder Full 1.00.8% adoption5active users
  3. Muse Wonder 1.00.5% adoption3active users
  4. Muse Wonder Full 1.0 Contributor0.3% adoption2active users
  5. Muse Wonder 1.0 Contributor0.2% adoption1active users
  6. Muse Wonder 1.0 High0.2% adoption1active users
All models

Sources and attribution

Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.

  • Epoch AIEpoch Capabilities Index, Epoch's own runs and the external results it collects.CC BY 4.0 · Retrieved Nov 12, 2026 · Data through Nov 9, 2026Epoch AI, ‘Capabilities & benchmarking’. Published online at epoch.ai. Retrieved from https://epoch.ai/benchmarks.
  • LMArenaWebDev Arena and Agent Arena leaderboards.CC BY 4.0 · Retrieved Oct 21, 2026 · Data through Oct 19, 2026LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), Hugging Face.
  • Terminal-BenchTerminal-Bench 4.1 official leaderboard rows (results only, no task content).Terms not stated · Retrieved Nov 12, 2026 · Data through Nov 11, 2026Terminal-Bench 4.1 leaderboard, tbench.ai. Every score links back to the leaderboard.
  • models.devSpecs and list prices per provider.MIT · Retrieved Nov 12, 2026models.dev, an open catalog of AI models (github.com/anomalyco/models.dev).
  • TokscaleActive users, tokens and token mix from public Tokscale submissions. Hidden accounts are excluded.How we count