Benchmark scores
Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.
LLM Comparison
Muse Wonder Full vs GPT-6.1 Sol: benchmark scores, pricing & comparison.
Side-by-side Muse Wonder Full vs GPT-6.1 Sol 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: Muse Wonder Full ranks higher (#6 vs #7) and wins 5 of 5 shared benchmarks.
Rank #6 vs #7AskClash overall scores 71.7 vs 71.4.
Pricing —/— vs $2.00/$10.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryMeta vs OpenAI.
Muse Wonder Full vs GPT-6.1 Sol benchmark comparison
Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.
| Metric | Muse Wonder Full | GPT-6.1 Sol |
|---|---|---|
| Overall Score | 71.7 | 71.4 |
| Leaderboard Rank | #6 | #7 |
| ACB | — | 69.9 |
| Coding Agent Index | — | 62.9 |
| HLE | 53.6 | 52.9 |
| GPQA | — | 95.0 |
| SWE-Atlas | — | 61.0 |
| Terminal-Bench | 57.1 | 56.1 |
| DeepSWE | 79.0 | 75.2 |
| GDPval-AA | 1857.1 | 1575.1 |
| Finance Agent | 59.1 | 52.0 |
| MMMU-Pro | — | 86.0 |
| ARC-AGI 2 | — | 94.2 |
| Input Price (per 1M tokens) | — | $2.00 |
| Output Price (per 1M tokens) | — | $10.0 |
| Context Window | 1M | 1.05M |
| Benchmarks Published | 8 | 14 |
Muse Wonder Full vs GPT-6.1 Sol head-to-head charts
Muse Wonder Full leads 6 and GPT-6.1 Sol leads 0 of 6 shared benchmarks. Charts show only benchmarks both models publish.
Muse Wonder FullGPT-6.1 Sol
Overall
HLE
Terminal-Bench
DeepSWE
GDPval-AA
Finance Agent
Muse Wonder Full
Input—
Output—
Workload—
Context1M
GPT-6.1 Sol
Input$2.00
Output$10.0
Workload$4.00
Context1.05M
Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.
More Muse Wonder Full and GPT-6.1 Sol comparisons
Explore how Muse Wonder Full and GPT-6.1 Sol stack up against other top-ranked LLMs.
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How to read this comparison
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.