LLM Comparison

GLM-5.3-Flash vs Muse Spark 1.2: benchmark scores, pricing & comparison.

Side-by-side GLM-5.3-Flash vs Muse Spark 1.2 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.

Rank #7 vs #15AskClash overall scores 71.8 vs 63.7.
Pricing $0.15/$0.50 vs $1.25/$4.25Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryZ.AI vs Meta.

GLM-5.3-Flash vs Muse Spark 1.2 benchmark comparison

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

MetricGLM-5.3-FlashMuse Spark 1.2
Overall Score71.863.7
Leaderboard Rank#7#15
ACB61.254.8
RWT8.57.5
HLE55.362.1
GPQA91.2
SWE-Pro61.5
Terminal-Bench84.380.0
DeepSWE63.459.0
GDPval-AA1773.01381.0
OSWorld80.8
MCP Atlas82.2
Finance Agent57.2
CharXiv89.488.4
MRCR54.1
Input Price (per 1M tokens)$0.15$1.25
Output Price (per 1M tokens)$0.50$4.25
Context Window1M1M
Benchmarks Published812

GLM-5.3-Flash vs Muse Spark 1.2 head-to-head charts

GLM-5.3-Flash leads 7 and Muse Spark 1.2 leads 1 of 8 shared benchmarks. GLM-5.3-Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GLM-5.3-FlashMuse Spark 1.2
Overall
71.8GLM-5.3-Flash
63.7Muse Spark 1.2
ACB
61.2GLM-5.3-Flash
54.8Muse Spark 1.2
RWT
8.5GLM-5.3-Flash
7.5Muse Spark 1.2
HLE
55.3GLM-5.3-Flash
62.1Muse Spark 1.2
Terminal-Bench
84.3GLM-5.3-Flash
80.0Muse Spark 1.2
DeepSWE
63.4GLM-5.3-Flash
59.0Muse Spark 1.2
GDPval-AA
1773.0GLM-5.3-Flash
1381.0Muse Spark 1.2
CharXiv
89.4GLM-5.3-Flash
88.4Muse Spark 1.2
GLM-5.3-Flash
Input$0.15
Output$0.50
Workload$0.25
Context1M
Muse Spark 1.2
Input$1.25
Output$4.25
Workload$2.10
Context1M

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

More GLM-5.3-Flash and Muse Spark 1.2 comparisons

Explore how GLM-5.3-Flash and Muse Spark 1.2 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.