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
#226
by active users
Active users
46
All time
Adoption
1.9%
of 2,457 accounts
Tokens
33.6B
cache included
Est. cost
$3.9K
at public list prices
First seen
Sep 2, 2026
in any submission

Oct 10, 2024 – Nov 12, 2026 (UTC)2,457 accounts100% of tokens from an identified modelData through Nov 12, 2026, 08:13 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, Oct 10, 2024 to Nov 12, 2026. Peak 8. 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
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Sep 2, 20263561K
Sep 3, 20264301.1M
Sep 4, 20264126.4M
Sep 5, 202623.8M
Sep 6, 2026115M
Sep 7, 202651.3B
Sep 8, 20264166.9M
Sep 9, 20265163.2M
Sep 10, 20268542.8M
Sep 11, 20266609.3M
Sep 12, 202651.5B
Sep 13, 20265902.6M
Sep 14, 20266622.6M
Sep 15, 20266624.8M
Sep 16, 20266447M
Sep 17, 202661.8B
Sep 18, 20266376.5M
Sep 19, 2026444.9M
Sep 20, 20262423.9M
Sep 21, 202641.1B
Sep 22, 20266269.5M
Sep 23, 20267100.8M
Sep 24, 2026367.9M
Sep 25, 2026140.9K
Sep 26, 2026314M
Sep 27, 20261324K
Sep 28, 20264205M
Sep 29, 2026357M
Sep 30, 20263384.6M
Oct 1, 20262934.4M
Oct 2, 20262271.1M
Oct 3, 20264340.2M
Oct 4, 20264376M
Oct 5, 202641.1B
Oct 6, 20265235.9M
Oct 7, 20268291.8M
Oct 8, 202651.2B
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Oct 10, 20265882.4M
Oct 11, 202641B
Oct 12, 202665.1B
Oct 13, 202652.3B
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Oct 15, 20264468.4M
Oct 16, 202661.2B
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Oct 18, 20264819K
Oct 19, 202648M
Oct 20, 2026422.7M
Oct 21, 20262633K
Oct 22, 20262402K
Oct 23, 2026540M
Oct 24, 20263873K
Oct 25, 202622.6M
Oct 26, 2026273.9K
Oct 27, 202621.8M
Oct 28, 202600
Oct 29, 20261158K
Oct 30, 2026136.2K
Oct 31, 20263742K
Nov 1, 202618.5K
Nov 2, 202652M
Nov 3, 2026320.1M
Nov 4, 20263542K
Nov 5, 20262190.2M
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 33.6B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input21%
  • Output0.5%
  • Cache read78%
  • Cache write0%
  • Reasoning<0.1%

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. Oh My Pi32% of this model's tokens10active users
  2. Codebuff30% of this model's tokens1active users
  3. OpenCode19% of this model's tokens11active users
  4. Muse Code14% of this model's tokens17active users
  5. Gajae Code3.0% of this model's tokens1active users
  6. Hermes Agent1.3% of this model's tokens4active users
  7. Pi0.5% of this model's tokens10active users
  8. Senpi (OmO Native)0.2% of this model's tokens2active users
  9. Reasonix<0.1% of this model's tokens1active users
  10. Cline<0.1% of this model's tokens1active users
  11. Codex CLI<0.1% of this model's tokens2active users
  12. DeepSeek Harness<0.1% of this model's tokens1active users
  13. Claude Code<0.1% of this model's tokens1active users
  14. Junie<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 14% of Muse Spark 1.3 tokens across all time (17 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
$0.40
Est. per 1M tokens
78% cache reads
At the community mix
$0.24
Est. per 1M tokens
93% cache reads
3:1 input/output blend
$2
Per 1M tokens at list prices
No cache

Cache reads were 78% of Muse Spark 1.3 tokens across all time and 93% 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 across all time.
  • The community mix is the tokens of every identified model across all time.
  • 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. 1Baptiste@BaptisteFaisy10.1Btokens—est. cost7active daysno price · 7 active days
  2. 2Owen@kang-heewon4.8Btokens—est. cost14active daysno price · 14 active days
  3. 3AJ@aj26663.8Btokens$1Kest. cost14active days$1K est. cost · 14 active days
  4. 4insterbridge@insterbridge3Btokens$1.3Kest. cost19active days$1.3K est. cost · 19 active days
  5. 5Zahar Izmailov@izzzzzi2Btokens—est. cost17active daysno price · 17 active days
  6. 6abilliontokens@abilliontokens1.9Btokens$354est. cost6active days$354 est. cost · 6 active days
  7. 7Sachee@comicsansbestfont1.9Btokens$96est. cost22active days$96 est. cost · 22 active days
  8. 8Khaliq@khaliqgant1.8Btokens$363est. cost12active days$363 est. cost · 12 active days
  9. 9luke eldridge@lkeld1.7Btokens$340est. cost8active days$340 est. cost · 8 active days
  10. 10Bellman@Yeachan-Heo1Btokens—est. cost3active daysno price · 3 active days

More from Meta

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

  1. Muse Spark 1.3 Contributor Free8.4% adoption206active users
  2. Muse Spark 1.3 Contributor5.6% adoption138active users
  3. Muse Spark 1.2 Contributor Free4.2% adoption103active users
  4. Muse Spark 1.2 Contributor3.4% adoption84active users
  5. Muse Spark 1.21.1% adoption27active users
  6. Muse Wonder 1.00.9% adoption21active 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