LLM Comparison

GPT-5.6 Sol vs Muse Wonder Full: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Sol vs Muse Wonder Full 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.

Verdict: GPT-5.6 Sol ranks higher (#10 vs #13); Muse Wonder Full wins 5 of 5 shared benchmarks.

Rank #10 vs #13AskClash overall scores 68.3 vs 62.7.
Pricing $5.00/$30.0 vs —/—Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Meta.

GPT-5.6 Sol vs Muse Wonder Full benchmark comparison

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

MetricGPT-5.6 SolMuse Wonder Full
Overall Score68.362.7
Leaderboard Rank#10#13
ACB63.2—
RWT9.5—
Coding Agent Index80.0—
HLE47.253.6
GPQA94.1—
IFEval72.7—
SWE-Pro64.6—
SWE-Atlas84.0—
Terminal-Bench39.957.1
DeepSWE72.779.0
GDPval-AA1748.01857.1
Finance Agent53.859.1
MMMU-Pro83.0—
ARC-AGI 292.5—
Tau285.1—
MRCR91.5—
Input Price (per 1M tokens)$5.00—
Output Price (per 1M tokens)$30.0—
Context Window1M1M
Benchmarks Published158

GPT-5.6 Sol vs Muse Wonder Full head-to-head charts

GPT-5.6 Sol leads 1 and Muse Wonder Full leads 5 of 6 shared benchmarks. Charts show only benchmarks both models publish.

GPT-5.6 SolMuse Wonder Full
Overall
68.3GPT-5.6 Sol
62.7Muse Wonder Full
HLE
47.2GPT-5.6 Sol
53.6Muse Wonder Full
Terminal-Bench
39.9GPT-5.6 Sol
57.1Muse Wonder Full
DeepSWE
72.7GPT-5.6 Sol
79.0Muse Wonder Full
GDPval-AA
1748.0GPT-5.6 Sol
1857.1Muse Wonder Full
Finance Agent
53.8GPT-5.6 Sol
59.1Muse Wonder Full
GPT-5.6 Sol
Input$5.00
Output$30.0
Workload$11
Context1M
Muse Wonder Full
Input—
Output—
Workload—
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 Wonder Full comparisons

Explore how GPT-5.6 Sol and Muse Wonder Full 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.