LLM Comparison

Muse Wonder vs GLM-5.3-Flash: benchmark scores, pricing & comparison.

Side-by-side Muse Wonder vs GLM-5.3-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 ranks higher (#11 vs #20); GLM-5.3-Flash costs less ($0.15/$0.50 vs $4.00/$20.0 per 1M tokens).

Rank #11 vs #20AskClash overall scores 64.7 vs 59.1.
Pricing $4.00/$20.0 vs $0.15/$0.50Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightMeta vs Z.AI.

Muse Wonder vs GLM-5.3-Flash benchmark comparison

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

MetricMuse WonderGLM-5.3-Flash
Overall Score64.759.1
Leaderboard Rank#11#20
ACB62.361.2
RWT—8.5
HLE50.155.3
GPQA—91.2
Terminal-Bench52.032.8
DeepSWE78.863.4
GDPval-AA1770.31773.0
Finance Agent56.657.9
CharXiv—89.4
Input Price (per 1M tokens)$4.00$0.15
Output Price (per 1M tokens)$20.0$0.50
Context Window1M1M
Benchmarks Published911

Muse Wonder vs GLM-5.3-Flash head-to-head charts

Muse Wonder leads 4 and GLM-5.3-Flash leads 3 of 7 shared benchmarks. GLM-5.3-Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Muse WonderGLM-5.3-Flash
Overall
64.7Muse Wonder
59.1GLM-5.3-Flash
ACB
62.3Muse Wonder
61.2GLM-5.3-Flash
HLE
50.1Muse Wonder
55.3GLM-5.3-Flash
Terminal-Bench
52.0Muse Wonder
32.8GLM-5.3-Flash
DeepSWE
78.8Muse Wonder
63.4GLM-5.3-Flash
GDPval-AA
1770.3Muse Wonder
1773.0GLM-5.3-Flash
Finance Agent
56.6Muse Wonder
57.9GLM-5.3-Flash
Muse Wonder
Input$4.00
Output$20.0
Workload$8.00
Context1M
GLM-5.3-Flash
Input$0.15
Output$0.50
Workload$0.25
Context1M

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

More Muse Wonder and GLM-5.3-Flash comparisons

Explore how Muse Wonder and GLM-5.3-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.