LLM Comparison

GLM-5.3-Flash vs DeepSeek V4 Flash 0731: benchmark scores, pricing & comparison.

Side-by-side GLM-5.3-Flash vs DeepSeek V4 Flash 0731 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 #23AskClash overall scores 71.8 vs 47.0.
Pricing $0.15/$0.50 vs $0.14/$0.28Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightZ.AI vs DeepSeek.

GLM-5.3-Flash vs DeepSeek V4 Flash 0731 benchmark comparison

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

MetricGLM-5.3-FlashDeepSeek V4 Flash 0731
Overall Score71.847.0
Leaderboard Rank#7#23
ACB61.248.0
RWT8.5
HLE55.337.0
GPQA91.291.0
SWE-bench79.0
Terminal-Bench84.382.7
DeepSWE63.454.4
GDPval-AA1773.0
MCP Atlas69.0
Finance Agent49.5
CharXiv89.4
MRCR78.7
Input Price (per 1M tokens)$0.15$0.14
Output Price (per 1M tokens)$0.50$0.28
Context Window1M1M
Benchmarks Published810

GLM-5.3-Flash vs DeepSeek V4 Flash 0731 head-to-head charts

GLM-5.3-Flash leads 6 and DeepSeek V4 Flash 0731 leads 0 of 6 shared benchmarks. DeepSeek V4 Flash 0731 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GLM-5.3-FlashDeepSeek V4 Flash 0731
Overall
71.8GLM-5.3-Flash
47.0DeepSeek V4 Flash 0731
ACB
61.2GLM-5.3-Flash
48.0DeepSeek V4 Flash 0731
HLE
55.3GLM-5.3-Flash
37.0DeepSeek V4 Flash 0731
GPQA
91.2GLM-5.3-Flash
91.0DeepSeek V4 Flash 0731
Terminal-Bench
84.3GLM-5.3-Flash
82.7DeepSeek V4 Flash 0731
DeepSWE
63.4GLM-5.3-Flash
54.4DeepSeek V4 Flash 0731
GLM-5.3-Flash
Input$0.15
Output$0.50
Workload$0.25
Context1M
DeepSeek V4 Flash 0731
Input$0.14
Output$0.28
Workload$0.20
Context1M

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

More GLM-5.3-Flash and DeepSeek V4 Flash 0731 comparisons

Explore how GLM-5.3-Flash and DeepSeek V4 Flash 0731 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.