[whatmodel.sh](../../README.md) / Muse Spark 1.1 # Muse Spark 1.1 Meta · released 2026-07 · closed weights **score 73.2** ±1.0 · #49 of 732 · from 9 benchmark results across 4 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at ● marks Muse Spark 1.1 among every model on that task or test, worst to best. 
task                vs the others         rank  counts  tests
agent tasks         ▁▁▃▆█▄▅▅●▄▂▁   #62 of 313*     32%      2
coding              ▁▁▁▃▅▇█▇▅●▃▁   #43 of 469*     17%      1
chat & writing      ▁▁▁▃▆▄▆█▆▇▇●   #13 of 402*     10%      1
math                ▁▁▃▅█▆▄█●▂▁▁   #39 of 431*     27%      2
vision & documents  ▁▁▂▂▁▃▄▂▆▇●▄   #23 of 153*     10%      2
agent tasks · #62 of 313 · 32% of its score Trails [Beam 1.0 501B A23B](beam-1-0-501b-a23b.md), [Claude Opus 4.5](claude-opus-4-5.md), [Claude Sonnet 4.6](claude-sonnet-4-6.md) here, though they rank lower overall. 
test                                     result  vs the others in its run  difficulty            counts  why
Arena Agent (October 2026 aggrega…  -0.0767 IPS  ▁▁▁●▃▂█▁▂▂▁▁ beats 8/59   avg -0.379 IPS           25%  sharp
τ³-bench banking_knowledge (v1.0.…        40.5%  ▃▃▂▃·▆▃▂█●▅▂ beats 20/25  very hard · avg 4.3%    6.5%  at its level
coding · #43 of 469 · 17% of its score Beats [GPT-5.5](gpt-5-5.md), [GPT-5.6 Terra](gpt-5-6-terra.md), [GPT-5.4](gpt-5-4.md) here, though they rank higher overall. Trails [Qwen3.8 27B](qwen3-8-27b.md), [GLM-5.2](glm-5-2.md), [GLM-5.3-Flash](glm-5-3-flash.md) here, though they rank lower overall. 
test                       result  vs the others in its run   difficulty  counts  why
Arena WebDev (Code Arena)  1542.5  ▁▁▃▂▅█▃●▅▅▁▂ beats 85/129  avg 981        17%  sharp
chat & writing · #13 of 402 · 10% of its score Beats [GPT-6 Astra](gpt-6-astra.md), [GPT-6.1 Sol](gpt-6-1-sol.md), [Claude Sonnet 5.5](claude-sonnet-5-5.md) here, though they rank higher overall. Trails [Muse Spark 1.2](muse-spark-1-2.md) here, though they rank lower overall. 
test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1490.2  ▁▁▁▂▃▃▃▆▆▇█● beats 373/385  avg 1260       10%  blunt
math · #39 of 431 · 27% of its score Beats [Claude Opus 4.7](claude-opus-4-7.md), [Grok 4.5](grok-4-5.md), [Claude Opus 4.6](claude-opus-4-6.md) here, though they rank higher overall. Trails [GPT-5.2](gpt-5-2.md), [Qwen3.7 Max](qwen3-7-max.md) here, though they rank lower overall. 
test                                result  vs the others in its run  difficulty            counts  why
MathArena ArXivMath June 2026 (48…   56.9%  ▂···▄·●█▆▆▄▂ beats 5/19   very hard · avg 5.1%     22%  sharp · at its level
MathArena BrokenArXiv June 2026 (…   50.6%  ▄··█▂▂▂●▄··▂ beats 10/14  very hard · avg 1.3%    4.9%  sharp · at its level · noisy
vision & documents · #23 of 153 · 10% of its score Beats [Claude Sonnet 5.5](claude-sonnet-5-5.md), [GPT-6 Sol](gpt-6-sol.md), [MiMo-V2.6-Pro](mimo-v2-6-pro.md) here, though they rank higher overall. Trails [Gemini 3.6 Flash](gemini-3-6-flash.md), [Gemini 3.5 Flash](gemini-3-5-flash.md), [Muse Spark 1.2](muse-spark-1-2.md) here, though they rank lower overall. 
test                               result  vs the others in its run    difficulty  counts  why
Arena vision (style controlled)    1280.0  ▁▁▂▂▂▂▃▄▅▅█● beats 131/152  avg 1061      6.6%  blunt
Arena document (style controlled)  1479.5  ▁▁▃▃▄▃▇█▅●▄▅ beats 29/37    avg 1331      3.4%  blunt
other tests (1) 
test               result  vs the others in its run  difficulty            counts  why
SimpleQA Verified   57.8%  ▁▁▃▂▃▃▆▆█●▂▅ beats 65/81  very hard · avg 8.0%    3.8%  at its level
## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md) 
source                                    results  share of the score
LMArena leaderboard dataset                     5   62% ▇▇▇▇▇▇▇
MathArena ArXivMath / BrokenArXiv / ArX…        2   27% ▇▇▇
τ²/τ³-bench leaderboard: Sierra's own e…        1    7% ▇
Epoch AI                                        1    4% ▇
prior: pull toward the middle                        0% ▇
weighted average                                   = 73.2
Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · MathArena ArXivMath / BrokenArXiv / ArXivLean model-output datasets ([CC BY-SA 4.0](../../licenses/matharena-sharealike-NOTICE.txt)) · τ²/τ³-bench leaderboard: Sierra's own evaluation runs ([MIT](https://opensource.org/license/mit)) · Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) ## How to run it ### Through an API api (Meta) · $2.00/M blended · $1.25 in / $4.25 out per 1M tokens · [dev.meta.ai](https://dev.meta.ai/docs) [price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/meta/models/muse-spark-1.1.toml): Standard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ. · [context source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/models/meta/muse-spark-1.1.toml) [interactive version](https://whatmodel.sh/model/muse-spark-1-1) · [JSON](https://whatmodel.sh/api?format=json&all=1)