[whatmodel.sh](../../README.md) / Muse Spark 1.2
# Muse Spark 1.2
Meta · released 2026-08 · closed weights
**score 72.9** ±1.1 · #51 of 732 · from 9 benchmark results across 3 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 1.2 among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄▅▅●▄▂▁ #61 of 313 47% 4
coding ▁▁▁▃▅▇█▇▅●▃▁ #46 of 469* 23% 1
chat & writing ▁▁▁▃▆▄▆█▆▇▇● #11 of 402* 13% 1
vision & documents ▁▁▂▂▁▃▄▂▆▇█● #10 of 153* 8.7% 1
web search ●··········█ #2 of 2* 2.9% 1
agent tasks · #61 of 313 · 47% of its score
Beats [Muse Spark 1.1](muse-spark-1-1.md) here, though they rank higher overall. 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… -0.0754 IPS ▁▁▁●▃▂█▁▂▂▁▁ beats 9/59 avg -0.379 IPS 33% sharp
Terminal-Bench 2.1 (maker) 82.9% ▁·▁·▁▁▄▃▆█●█ beats 48/63 hard · avg 26% 6.4% sharp · small run
JobBench (maker) 61.6% ●·█····█···█ beats 0/3 hard · avg 25% 4.3% at its level
DeepSearchQA (maker) 85.9% ▄·▄▄···▄●··█ beats 4/6 medium · avg 54% 2.9% small run
coding · #46 of 469 · 23% 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), [Gemini 3.6 Flash](gemini-3-6-flash.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena WebDev (Code Arena) 1533.7 ▁▁▃▂▅█▃●▅▅▁▂ beats 82/129 avg 981 23% sharp
chat & writing · #11 of 402 · 13% 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.
test result vs the others in its run difficulty counts why
LMArena (text) 1492.2 ▁▁▁▂▃▃▃▆▆▇█● beats 375/385 avg 1260 13% blunt
vision & documents · #10 of 153 · 8.7% of its score
Beats [GPT-6 Astra](gpt-6-astra.md), [Claude Fable 5.1](claude-fable-5-1.md), [Claude Sonnet 5.5](claude-sonnet-5-5.md) here, though they rank higher overall.
test result vs the others in its run difficulty counts why
Arena vision (style controlled) 1292.7 ▁▁▂▂▂▂▃▄▅▅█● beats 144/152 avg 1061 8.7% blunt
web search · #2 of 2 · 2.9% of its score
test result vs the others in its run difficulty counts why
DeepSearchQA (maker) 85.9% ▄·▄▄···▄●··█ beats 4/6 medium · avg 54% 2.9% small run
other tests (2)
test result vs the others in its run difficulty counts why
SimpleQA Verified 60.3% ▁▁▃▂▃▃▆▆█●▂▅ beats 67/81 very hard · avg 8.0% 5.1% at its level
AutomationBench public set (Zapie… 38.2% ●······▄█··█ beats 1/6 very hard · avg 13% 2.2% at its level · small run
source results share of the score
LMArena leaderboard dataset 4 79% ▇▇▇▇▇▇▇▇▇
Meta vendor-reported benchmark scores f… 4 16% ▇▇
Epoch AI 1 5% ▇
prior: pull toward the middle 1% ▇
weighted average = 72.9
Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · 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-1.2.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-1.2.toml)
[interactive version](https://whatmodel.sh/model/muse-spark-1-2) · [JSON](https://whatmodel.sh/api?format=json&all=1)