LLM Comparison

Claude Fable 5.1 vs GLM-5.3: benchmark scores, pricing & comparison.

Side-by-side Claude Fable 5.1 vs GLM-5.3 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 #1 vs #4AskClash overall scores 92.0 vs 80.4.
Pricing $10.0/$50.0 vs $1.40/$4.40Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightAnthropic vs Z.AI.

Claude Fable 5.1 vs GLM-5.3 benchmark comparison

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

MetricClaude Fable 5.1GLM-5.3
Overall Score92.080.4
Leaderboard Rank#1#4
ACB79.262.2
RWT9.08.5
HLE65.062.5
GPQA93.791.7
SWE-Pro81.2
Terminal-Bench91.488.2
DeepSWE67.469.0
GDPval-AA1853.01769.0
Finance Agent58.955.8
MMMU-Pro90.6
ARC-AGI 290.0
Input Price (per 1M tokens)$10.0$1.40
Output Price (per 1M tokens)$50.0$4.40
Context Window1M1M
Benchmarks Published118

Claude Fable 5.1 vs GLM-5.3 head-to-head charts

Claude Fable 5.1 leads 8 and GLM-5.3 leads 1 of 9 shared benchmarks. GLM-5.3 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Fable 5.1GLM-5.3
Overall
92.0Claude Fable 5.1
80.4GLM-5.3
ACB
79.2Claude Fable 5.1
62.2GLM-5.3
RWT
9.0Claude Fable 5.1
8.5GLM-5.3
HLE
65.0Claude Fable 5.1
62.5GLM-5.3
GPQA
93.7Claude Fable 5.1
91.7GLM-5.3
Terminal-Bench
91.4Claude Fable 5.1
88.2GLM-5.3
DeepSWE
67.4Claude Fable 5.1
69.0GLM-5.3
GDPval-AA
1853.0Claude Fable 5.1
1769.0GLM-5.3
Finance Agent
58.9Claude Fable 5.1
55.8GLM-5.3
Claude Fable 5.1
Input$10.0
Output$50.0
Workload$20
Context1M
GLM-5.3
Input$1.40
Output$4.40
Workload$2.28
Context1M

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

More Claude Fable 5.1 and GLM-5.3 comparisons

Explore how Claude Fable 5.1 and GLM-5.3 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.