Compare · ModelsLive · 2 picked · head to head
Claude Opus 4.5 vs GLM 5
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Opus 4.5 wins on 14/16 benchmarks
Claude Opus 4.5 wins 14 of 16 shared benchmarks. Leads in agentic · reasoning · arena.
Category leads
agentic·Claude Opus 4.5reasoning·Claude Opus 4.5arena·Claude Opus 4.5knowledge·Claude Opus 4.5general·Claude Opus 4.5math·Claude Opus 4.5coding·Claude Opus 4.5
Hype vs Reality
Attention vs performance
Claude Opus 4.5
#185 by perf·#9 by attention
GLM 5
#83 by perf·#3 by attention
Best value
GLM 5
9.5x better value than Claude Opus 4.5
Claude Opus 4.5
2.8 pts/$
$15.00/M
GLM 5
26.2 pts/$
$2.10/M
Vendor risk
Who is behind the model
Anthropic
$965.0B·Tier 1
z-ai
private · undisclosed
Head to head
16 benchmarks · 2 models
Claude Opus 4.5GLM 5
APEX-Agents
Claude Opus 4.5 leads by +1.2
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Claude Opus 4.5
18.4
GLM 5
17.2
ARC-AGI
Claude Opus 4.5 leads by +35.3
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Claude Opus 4.5
80.0
GLM 5
44.7
ARC-AGI-2
Claude Opus 4.5 leads by +32.8
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
Claude Opus 4.5
37.6
GLM 5
4.9
Chatbot Arena Elo · Coding
Claude Opus 4.5 leads by +34.4
Claude Opus 4.5
1468.5
GLM 5
1434.0
Chatbot Arena Elo · Overall
Claude Opus 4.5 leads by +12.2
Claude Opus 4.5
1469.8
GLM 5
1457.6
Chess Puzzles
Claude Opus 4.5 leads by +4.2
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Claude Opus 4.5
9.5
GLM 5
5.3
Cl Bench
Claude Opus 4.5 leads by +2.4
Claude Opus 4.5
21.1
GLM 5
18.7
FrontierMath-2025-02-28-Private
GLM 5 leads by +8.1
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Claude Opus 4.5
20.7
GLM 5
28.8
FrontierMath-Tier-4-2025-07-01-Private
Claude Opus 4.5 leads by +0.7
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Claude Opus 4.5
4.2
GLM 5
3.5
GPQA diamond
GLM 5 leads by +2.4
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Claude Opus 4.5
81.4
GLM 5
83.8
OTIS Mock AIME 2024-2025
Claude Opus 4.5 leads by +6.1
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Opus 4.5
86.1
GLM 5
80.0
PostTrainBench
Claude Opus 4.5 leads by +3.4
Claude Opus 4.5
17.3
GLM 5
13.9
SimpleBench
Claude Opus 4.5 leads by +10.6
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Opus 4.5
54.4
GLM 5
43.8
SWE-Bench verified
Claude Opus 4.5 leads by +4.6
SWE-bench Verified · 500 human-validated tasks from 12 real Python repositories (Django, Flask, scikit-learn, sympy, and others). Each task requires the model to produce a git patch that resolves a real GitHub issue and passes the test suite. The verified subset eliminates ambiguous tasks from the original SWE-bench. Claude Mythos Preview leads at 93.9%, crossing 90% for the first time in 2026. Opus 4.6 scores 80.8%. The benchmark remains the most-cited evaluation for code-generation capability.
Claude Opus 4.5
76.7
GLM 5
72.1
Terminal Bench
Claude Opus 4.5 leads by +10.7
Terminal-Bench 2.0 · evaluates AI agents on real terminal-based coding tasks · writing scripts, debugging, running tests, and managing projects entirely through command-line interaction. Tests both code quality and terminal fluency. Claude Opus 4.7 scores 69.4%, demonstrating significant agentic terminal competence.
Claude Opus 4.5
63.1
GLM 5
52.4
WeirdML
Claude Opus 4.5 leads by +15.6
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Claude Opus 4.5
63.7
GLM 5
48.2
Full benchmark table
| Benchmark | Claude Opus 4.5 | GLM 5 |
|---|---|---|
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 18.4 | 17.2 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | 80.0 | 44.7 |
ARC-AGI-2 ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data. | 37.6 | 4.9 |
Chatbot Arena Elo · Coding | 1468.5 | 1434.0 |
Chatbot Arena Elo · Overall | 1469.8 | 1457.6 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 9.5 | 5.3 |
Cl Bench | 21.1 | 18.7 |
FrontierMath-2025-02-28-Private FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning. | 20.7 | 28.8 |
FrontierMath-Tier-4-2025-07-01-Private FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning. | 4.2 | 3.5 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 81.4 | 83.8 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 86.1 | 80.0 |
PostTrainBench | 17.3 | 13.9 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 54.4 | 43.8 |
SWE-Bench verified SWE-bench Verified · 500 human-validated tasks from 12 real Python repositories (Django, Flask, scikit-learn, sympy, and others). Each task requires the model to produce a git patch that resolves a real GitHub issue and passes the test suite. The verified subset eliminates ambiguous tasks from the original SWE-bench. Claude Mythos Preview leads at 93.9%, crossing 90% for the first time in 2026. Opus 4.6 scores 80.8%. The benchmark remains the most-cited evaluation for code-generation capability. | 76.7 | 72.1 |
Terminal Bench Terminal-Bench 2.0 · evaluates AI agents on real terminal-based coding tasks · writing scripts, debugging, running tests, and managing projects entirely through command-line interaction. Tests both code quality and terminal fluency. Claude Opus 4.7 scores 69.4%, demonstrating significant agentic terminal competence. | 63.1 | 52.4 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 63.7 | 48.2 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $5.00 | $25.00 | 200K tokens (~100 books) | $100.00 | |
| $1.00 | $3.20 | 205K tokens (~102 books) | $15.50 |
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