LLM Comparison

GPT-5.5 vs Muse Spark 1.2: benchmark scores, pricing & comparison.

Side-by-side GPT-5.5 vs Muse Spark 1.2 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Rank #7 vs #12AskClash overall scores 72.5 vs 70.4.
Pricing $5.00/$30.0 vs $1.25/$4.25Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Meta.

GPT-5.5 vs Muse Spark 1.2 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricGPT-5.5Muse Spark 1.2
Overall Score72.570.4
Leaderboard Rank#7#12
RWT8.07.5
Coding Agent Index61.5
HLE52.262.1
GPQA93.6
SWE-Pro58.661.5
Terminal-Bench82.780.0
DeepSWE67.059.0
OSWorld78.780.8
MCP Atlas75.382.2
Finance Agent51.857.2
CharXiv88.4
MMMU-Pro81.2
ARC-AGI 285.0
Tau298.0
MRCR54.1
Input Price (per 1M tokens)$5.00$1.25
Output Price (per 1M tokens)$30.0$4.25
Context Window1M1M
Benchmarks Published1411

GPT-5.5 vs Muse Spark 1.2 head-to-head charts

GPT-5.5 leads 4 and Muse Spark 1.2 leads 5 of 9 shared benchmarks. Muse Spark 1.2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.5Muse Spark 1.2
Overall
72.5GPT-5.5
70.4Muse Spark 1.2
RWT
8.0GPT-5.5
7.5Muse Spark 1.2
HLE
52.2GPT-5.5
62.1Muse Spark 1.2
SWE-Pro
58.6GPT-5.5
61.5Muse Spark 1.2
Terminal-Bench
82.7GPT-5.5
80.0Muse Spark 1.2
DeepSWE
67.0GPT-5.5
59.0Muse Spark 1.2
OSWorld
78.7GPT-5.5
80.8Muse Spark 1.2
MCP Atlas
75.3GPT-5.5
82.2Muse Spark 1.2
Finance Agent
51.8GPT-5.5
57.2Muse Spark 1.2
GPT-5.5
Input$5.00
Output$30.0
Workload$11
Context1M
Muse Spark 1.2
Input$1.25
Output$4.25
Workload$2.10
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More GPT-5.5 and Muse Spark 1.2 comparisons

Explore how GPT-5.5 and Muse Spark 1.2 stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.