LLM Comparison

GPT-5.6 Sol vs Muse Spark 1.2: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Sol 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 #4 vs #31AskClash overall scores 71.2 vs 56.3.
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-5.6 Sol 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-5.6 SolMuse Spark 1.2
Overall Score71.256.3
Leaderboard Rank#4#31
ACB63.254.8
RWT9.57.5
Coding Agent Index80.0
HLE47.245.5
GPQA94.190.4
IFEval72.7
SWE-Pro64.6
SWE-Atlas84.0
Terminal-Bench88.8
DeepSWE72.759.0
GDPval-AA1748.01523.3
MCP Atlas82.2
Finance Agent53.860.6
MMMU-Pro83.0
ARC-AGI 292.5
Tau285.1
MRCR91.5
Input Price (per 1M tokens)$5.00$1.25
Output Price (per 1M tokens)$30.0$4.25
Context Window1M1M
Benchmarks Published168

GPT-5.6 Sol vs Muse Spark 1.2 head-to-head charts

GPT-5.6 Sol leads 7 and Muse Spark 1.2 leads 1 of 8 shared benchmarks. Muse Spark 1.2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 SolMuse Spark 1.2
Overall
71.2GPT-5.6 Sol
56.3Muse Spark 1.2
ACB
63.2GPT-5.6 Sol
54.8Muse Spark 1.2
RWT
9.5GPT-5.6 Sol
7.5Muse Spark 1.2
HLE
47.2GPT-5.6 Sol
45.5Muse Spark 1.2
GPQA
94.1GPT-5.6 Sol
90.4Muse Spark 1.2
DeepSWE
72.7GPT-5.6 Sol
59.0Muse Spark 1.2
GDPval-AA
1748.0GPT-5.6 Sol
1523.3Muse Spark 1.2
Finance Agent
53.8GPT-5.6 Sol
60.6Muse Spark 1.2
GPT-5.6 Sol
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-5.6 Sol and Muse Spark 1.2 comparisons

Explore how GPT-5.6 Sol 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.