LLM Comparison

Muse Wonder Full vs DeepSeek V4.1 Flash: benchmark scores, pricing & comparison.

Side-by-side Muse Wonder Full vs DeepSeek V4.1 Flash 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 #22) and wins 5 of 5 shared benchmarks.

Rank #6 vs #22AskClash overall scores 71.7 vs 58.5.
Pricing —/— vs $0.15/$0.60Input and output token prices per 1M tokens when published.
Proprietary vs APIMeta vs DeepSeek.

Muse Wonder Full vs DeepSeek V4.1 Flash benchmark comparison

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

MetricMuse Wonder FullDeepSeek V4.1 Flash
Overall Score71.758.5
Leaderboard Rank#6#22
ACB—63.0
HLE53.636.8
GPQA—90.9
Terminal-Bench57.126.8
DeepSWE79.074.2
GDPval-AA1857.11600.0
Finance Agent59.153.5
MMMU-Pro—77.0
Input Price (per 1M tokens)—$0.15
Output Price (per 1M tokens)—$0.60
Context Window1M1M
Benchmarks Published811

Muse Wonder Full vs DeepSeek V4.1 Flash head-to-head charts

Muse Wonder Full leads 6 and DeepSeek V4.1 Flash leads 0 of 6 shared benchmarks. Charts show only benchmarks both models publish.

Muse Wonder FullDeepSeek V4.1 Flash
Overall
71.7Muse Wonder Full
58.5DeepSeek V4.1 Flash
HLE
53.6Muse Wonder Full
36.8DeepSeek V4.1 Flash
Terminal-Bench
57.1Muse Wonder Full
26.8DeepSeek V4.1 Flash
DeepSWE
79.0Muse Wonder Full
74.2DeepSeek V4.1 Flash
GDPval-AA
1857.1Muse Wonder Full
1600.0DeepSeek V4.1 Flash
Finance Agent
59.1Muse Wonder Full
53.5DeepSeek V4.1 Flash
Muse Wonder Full
Input—
Output—
Workload—
Context1M
DeepSeek V4.1 Flash
Input$0.15
Output$0.60
Workload$0.27
Context1M

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

More Muse Wonder Full and DeepSeek V4.1 Flash comparisons

Explore how Muse Wonder Full and DeepSeek V4.1 Flash 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.