LLM Comparison

Grok 4.5 vs GLM 5.1 Thinking: benchmark scores, pricing & comparison.

Side-by-side Grok 4.5 vs GLM 5.1 Thinking 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 #10 vs #25AskClash overall scores 70.1 vs 50.5.
Pricing $2.00/$6.00 vs $0/$0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryxAI vs Zhipu AI.

Grok 4.5 vs GLM 5.1 Thinking benchmark comparison

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

MetricGrok 4.5GLM 5.1 Thinking
Overall Score70.150.5
Leaderboard Rank#10#25
RWT9.0
Coding Agent Index76.436.1
HLE40.352.3
GPQA93.186.2
SWE-Pro64.758.4
SWE-Atlas83.9
Terminal-Bench83.363.5
MCP Atlas71.8
Finance Agent48.344.8
MMMU-Pro80.4
ARC-AGI 252.6
Tau297.7
Input Price (per 1M tokens)$2.00$0
Output Price (per 1M tokens)$6.00$0
Context Window500K203K
Benchmarks Published129

Grok 4.5 vs GLM 5.1 Thinking head-to-head charts

Grok 4.5 leads 6 and GLM 5.1 Thinking leads 1 of 7 shared benchmarks. GLM 5.1 Thinking is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.5GLM 5.1 Thinking
Overall
70.1Grok 4.5
50.5GLM 5.1 Thinking
Coding Agent Index
76.4Grok 4.5
36.1GLM 5.1 Thinking
HLE
40.3Grok 4.5
52.3GLM 5.1 Thinking
GPQA
93.1Grok 4.5
86.2GLM 5.1 Thinking
SWE-Pro
64.7Grok 4.5
58.4GLM 5.1 Thinking
Terminal-Bench
83.3Grok 4.5
63.5GLM 5.1 Thinking
Finance Agent
48.3Grok 4.5
44.8GLM 5.1 Thinking
Grok 4.5
Input$2.00
Output$6.00
Workload$3.20
Context500K
GLM 5.1 Thinking
Input$0
Output$0
Workload$0.00
Context203K

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

More Grok 4.5 and GLM 5.1 Thinking comparisons

Explore how Grok 4.5 and GLM 5.1 Thinking 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.