LLM Comparison

GLM-5.3 vs Claude Opus 4.8: benchmark scores, pricing & comparison.

Side-by-side GLM-5.3 vs Claude Opus 4.8 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 #3 vs #8AskClash overall scores 80.4 vs 73.8.
Pricing $1.40/$4.40 vs $5.00/$25.0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryZ.AI vs Anthropic.

GLM-5.3 vs Claude Opus 4.8 benchmark comparison

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

MetricGLM-5.3Claude Opus 4.8
Overall Score80.473.8
Leaderboard Rank#3#8
ACB62.260.1
RWT8.59.0
Coding Agent Index72.5
HLE62.557.9
GPQA91.793.6
IFEval62.2
SWE-bench88.6
SWE-Pro69.2
SWE-Atlas82.5
Terminal-Bench88.274.6
DeepSWE66.959.0
OSWorld83.4
MCP Atlas82.2
Finance Agent53.9
CharXiv89.9
ARC-AGI 272.1
Tau294.4
Input Price (per 1M tokens)$1.40$5.00
Output Price (per 1M tokens)$4.40$25.0
Context Window1M1M
Benchmarks Published718

GLM-5.3 vs Claude Opus 4.8 head-to-head charts

GLM-5.3 leads 5 and Claude Opus 4.8 leads 2 of 7 shared benchmarks. GLM-5.3 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GLM-5.3Claude Opus 4.8
Overall
80.4GLM-5.3
73.8Claude Opus 4.8
ACB
62.2GLM-5.3
60.1Claude Opus 4.8
RWT
8.5GLM-5.3
9.0Claude Opus 4.8
HLE
62.5GLM-5.3
57.9Claude Opus 4.8
GPQA
91.7GLM-5.3
93.6Claude Opus 4.8
Terminal-Bench
88.2GLM-5.3
74.6Claude Opus 4.8
DeepSWE
66.9GLM-5.3
59.0Claude Opus 4.8
GLM-5.3
Input$1.40
Output$4.40
Workload$2.28
Context1M
Claude Opus 4.8
Input$5.00
Output$25.0
Workload$10
Context1M

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

More GLM-5.3 and Claude Opus 4.8 comparisons

Explore how GLM-5.3 and Claude Opus 4.8 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.