LLM Comparison

GPT-6.1 Sol vs Muse Wonder: benchmark scores, pricing & comparison.

Side-by-side GPT-6.1 Sol vs Muse Wonder 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-6.1 Sol ranks higher (#7 vs #11); GPT-6.1 Sol costs less ($2.00/$10.0 vs $4.00/$20.0 per 1M tokens).

Rank #7 vs #11AskClash overall scores 71.4 vs 64.7.
Pricing $2.00/$10.0 vs $4.00/$20.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Meta.

GPT-6.1 Sol vs Muse Wonder benchmark comparison

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

MetricGPT-6.1 SolMuse Wonder
Overall Score71.464.7
Leaderboard Rank#7#11
ACB69.962.3
Coding Agent Index62.9—
HLE52.950.1
GPQA95.0—
SWE-Atlas61.0—
Terminal-Bench56.152.0
DeepSWE75.278.8
GDPval-AA1575.11770.3
Finance Agent52.056.6
MMMU-Pro86.0—
ARC-AGI 294.2—
Input Price (per 1M tokens)$2.00$4.00
Output Price (per 1M tokens)$10.0$20.0
Context Window1.05M1M
Benchmarks Published149

GPT-6.1 Sol vs Muse Wonder head-to-head charts

GPT-6.1 Sol leads 4 and Muse Wonder leads 3 of 7 shared benchmarks. GPT-6.1 Sol is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-6.1 SolMuse Wonder
Overall
71.4GPT-6.1 Sol
64.7Muse Wonder
ACB
69.9GPT-6.1 Sol
62.3Muse Wonder
HLE
52.9GPT-6.1 Sol
50.1Muse Wonder
Terminal-Bench
56.1GPT-6.1 Sol
52.0Muse Wonder
DeepSWE
75.2GPT-6.1 Sol
78.8Muse Wonder
GDPval-AA
1575.1GPT-6.1 Sol
1770.3Muse Wonder
Finance Agent
52.0GPT-6.1 Sol
56.6Muse Wonder
GPT-6.1 Sol
Input$2.00
Output$10.0
Workload$4.00
Context1.05M
Muse Wonder
Input$4.00
Output$20.0
Workload$8.00
Context1M

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

More GPT-6.1 Sol and Muse Wonder comparisons

Explore how GPT-6.1 Sol and Muse Wonder 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.