LLM Comparison

GLM-5.3-Flash vs Gemini 3.1 Pro: benchmark scores, pricing & comparison.

Side-by-side GLM-5.3-Flash vs Gemini 3.1 Pro 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 #29AskClash overall scores 71.8 vs 37.5.
Pricing $0.15/$0.50 vs $2.00/$12.0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryZ.AI vs Google.

GLM-5.3-Flash vs Gemini 3.1 Pro benchmark comparison

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

MetricGLM-5.3-FlashGemini 3.1 Pro
Overall Score71.837.5
Leaderboard Rank#7#29
ACB61.2
RWT8.5
Coding Agent Index32.9
HLE55.351.4
GPQA91.294.3
SWE-bench80.6
SWE-Pro54.2
Terminal-Bench84.368.5
DeepSWE63.411.7
GDPval-AA1773.01317.0
MCP Atlas69.2
Finance Agent43.0
CharXiv89.480.2
MMMU-Pro83.9
ARC-AGI 277.1
Tau299.3
MRCR84.9
Input Price (per 1M tokens)$0.15$2.00
Output Price (per 1M tokens)$0.50$12.0
Context Window1M1M
Benchmarks Published816

GLM-5.3-Flash vs Gemini 3.1 Pro head-to-head charts

GLM-5.3-Flash leads 6 and Gemini 3.1 Pro leads 1 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.

GLM-5.3-FlashGemini 3.1 Pro
Overall
71.8GLM-5.3-Flash
37.5Gemini 3.1 Pro
HLE
55.3GLM-5.3-Flash
51.4Gemini 3.1 Pro
GPQA
91.2GLM-5.3-Flash
94.3Gemini 3.1 Pro
Terminal-Bench
84.3GLM-5.3-Flash
68.5Gemini 3.1 Pro
DeepSWE
63.4GLM-5.3-Flash
11.7Gemini 3.1 Pro
GDPval-AA
1773.0GLM-5.3-Flash
1317.0Gemini 3.1 Pro
CharXiv
89.4GLM-5.3-Flash
80.2Gemini 3.1 Pro
GLM-5.3-Flash
Input$0.15
Output$0.50
Workload$0.25
Context1M
Gemini 3.1 Pro
Input$2.00
Output$12.0
Workload$4.40
Context1M

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

More GLM-5.3-Flash and Gemini 3.1 Pro comparisons

Explore how GLM-5.3-Flash and Gemini 3.1 Pro 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.