LLM Comparison

GPT-6 Astra vs Muse Wonder Full: benchmark scores, pricing & comparison.

Side-by-side GPT-6 Astra 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-6 Astra ranks higher (#7 vs #13); Muse Wonder Full wins 3 of 5 shared benchmarks.

Rank #7 vs #13AskClash overall scores 70.0 vs 62.7.
Pricing $10.0/$50.0 vs —/—Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Meta.

GPT-6 Astra 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-6 AstraMuse Wonder Full
Overall Score70.062.7
Leaderboard Rank#7#13
ACB64.5—
RWT9.5—
Coding Agent Index67.0—
HLE57.253.6
GPQA96.0—
Terminal-Bench59.157.1
DeepSWE73.279.0
GDPval-AA1629.31857.1
Finance Agent53.559.1
MMMU-Pro87.0—
ARC-AGI 295.0—
MRCR100.0—
Input Price (per 1M tokens)$10.0—
Output Price (per 1M tokens)$50.0—
Context Window1.05M1M
Benchmarks Published138

GPT-6 Astra vs Muse Wonder Full head-to-head charts

GPT-6 Astra leads 3 and Muse Wonder Full leads 3 of 6 shared benchmarks. Charts show only benchmarks both models publish.

GPT-6 AstraMuse Wonder Full
Overall
70.0GPT-6 Astra
62.7Muse Wonder Full
HLE
57.2GPT-6 Astra
53.6Muse Wonder Full
Terminal-Bench
59.1GPT-6 Astra
57.1Muse Wonder Full
DeepSWE
73.2GPT-6 Astra
79.0Muse Wonder Full
GDPval-AA
1629.3GPT-6 Astra
1857.1Muse Wonder Full
Finance Agent
53.5GPT-6 Astra
59.1Muse Wonder Full
GPT-6 Astra
Input$10.0
Output$50.0
Workload$20
Context1.05M
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-6 Astra and Muse Wonder Full comparisons

Explore how GPT-6 Astra 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.