AI model matchup

Muse Spark 1.1 vs Muse Spark 1.2

A side-by-side look at published capability scores, listed API pricing, speed, context, and license - to help you decide which trade-offs fit your work.

OpenAI

GPT-5.6 Sol

Rank #1 • Score 57.2
Comparison Metrics
Speed: 89c/s vs 68c/s
Pricing: $7.78 vs $7.22
Anthropic

Claude Opus 5

Rank #2 • Score 56.2

Muse Spark 1.1vsMuse Spark 1.2

Muse Spark 1.2 leads the RankLLMs Index by 0.3 points (53.5 vs 53.2). Verified API Pricing: $1.25 (Muse Spark 1.1) vs $1.25 (Muse Spark 1.2) per 1M tokens.

Capability profile

Muse Spark 1.1Muse Spark 1.2

Speed duel

tps
Muse Spark 1.1140
Muse Spark 1.2143

Price duel

$/1M
Muse Spark 1.1$1.25
Muse Spark 1.2$1.25

Shorter bar = cheaper. Blended per 1M tokens.

MetricMuse Spark 1.1Muse Spark 1.2
RankLLMs Overall Score53.2 pts 53.5 pts ▲
Reasoning62.1 ▲57.0
Coding61.5 ▲59.3
Agentic Tool Use54.7 ▲48.5
Code Arena Elo1371 1631 ▲
Inference Speed140 tps 143 tps ▲
API Price (per 1M tokens)$1.25 $1.25
Context Window1M 1M
LicenseProprietary Proprietary
Global Rank#27 #26 ▲

Decision notes

What the numbers suggest

Muse Spark 1.2 leads the RankLLMs overall score by 0.3 points. The overall score is only one signal; compare the capability scores and model terms against your own workload.

Treat the overall index as a starting point, then prioritize the benchmark that resembles your task. Published scores and provider pricing can change; this comparison does not represent a first-party test of either model.

Overall index
Muse Spark 1.2 leads
53.2 to 53.5 pts
Coding score
Muse Spark 1.1 leads
61.5 to 59.3 pts
Reasoning score
Muse Spark 1.1 leads
62.1 to 57.0 pts
Agentic score
Muse Spark 1.1 leads
54.7 to 48.5 pts

Choose by workload

Which profile fits your use?

Meta

Consider Muse Spark 1.1 when

your workload gives more weight to the higher listed coding score, the higher listed reasoning score. Compare those signals with your own task mix, latency needs, and budget.

View Muse Spark 1.1 profile

Meta

Consider Muse Spark 1.2 when

your workload gives more weight to the higher overall index score. Compare those signals with your own task mix, latency needs, and budget.

View Muse Spark 1.2 profile

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