Compare · ModelsLive · 2 picked · head to head
GLM 5 vs GPT-5.4
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
GPT-5.4 wins on 14/15 benchmarks
GPT-5.4 wins 14 of 15 shared benchmarks. Leads in agentic · reasoning · knowledge.
Category leads
agentic·GPT-5.4reasoning·GPT-5.4arena·GLM 5knowledge·GPT-5.4general·GPT-5.4math·GPT-5.4coding·GPT-5.4
Hype vs Reality
Attention vs performance
GLM 5
#90 by perf·#3 by attention
GPT-5.4
#114 by perf·#9 by attention
Best value
GLM 5
4.4x better value than GPT-5.4
GLM 5
26.0 pts/$
$2.10/M
GPT-5.4
6.0 pts/$
$8.75/M
Vendor risk
Who is behind the model
z-ai
private · undisclosed
OpenAI
$840.0B·Tier 1
Head to head
15 benchmarks · 2 models
GLM 5GPT-5.4
APEX-Agents
GPT-5.4 leads by +35.2
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
GLM 5
17.2
GPT-5.4
52.4
ARC-AGI
GPT-5.4 leads by +49.0
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
GLM 5
44.7
GPT-5.4
93.7
ARC-AGI-2
GPT-5.4 leads by +69.1
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
GLM 5
4.9
GPT-5.4
74.0
Chatbot Arena Elo · Coding
GLM 5 leads by +39.0
GLM 5
1434.0
GPT-5.4
1395.0
Chatbot Arena Elo · Overall
GPT-5.4 leads by +7.2
GLM 5
1457.6
GPT-5.4
1464.8
Chess Puzzles
GPT-5.4 leads by +35.3
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
GLM 5
10.0
GPT-5.4
45.3
Cl Bench
GPT-5.4 leads by +9.2
GLM 5
18.7
GPT-5.4
27.9
FrontierMath-2025-02-28-Private
GPT-5.4 leads by +31.2
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
GLM 5
16.4
GPT-5.4
47.6
FrontierMath-Tier-4-2025-07-01-Private
GPT-5.4 leads by +25.0
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
GLM 5
2.1
GPT-5.4
27.1
GPQA diamond
GPT-5.4 leads by +11.1
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
GLM 5
83.8
GPT-5.4
94.9
OTIS Mock AIME 2024-2025
GPT-5.4 leads by +17.8
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
GLM 5
80.0
GPT-5.4
97.8
PostTrainBench
GPT-5.4 leads by +6.3
GLM 5
13.9
GPT-5.4
20.2
SWE-Bench verified
GPT-5.4 leads by +4.8
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. The benchmark remains the most-cited evaluation for code-generation capability.
GLM 5
72.1
GPT-5.4
76.9
Terminal Bench
GPT-5.4 leads by +29.4
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.
GLM 5
52.4
GPT-5.4
81.8
WeirdML
GPT-5.4 leads by +9.3
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
GLM 5
48.2
GPT-5.4
57.4
Full benchmark table
| Benchmark | GLM 5 | GPT-5.4 |
|---|---|---|
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 17.2 | 52.4 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | 44.7 | 93.7 |
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. | 4.9 | 74.0 |
Chatbot Arena Elo · Coding | 1434.0 | 1395.0 |
Chatbot Arena Elo · Overall | 1457.6 | 1464.8 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 10.0 | 45.3 |
Cl Bench | 18.7 | 27.9 |
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. | 16.4 | 47.6 |
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. | 2.1 | 27.1 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 83.8 | 94.9 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 80.0 | 97.8 |
PostTrainBench | 13.9 | 20.2 |
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. The benchmark remains the most-cited evaluation for code-generation capability. | 72.1 | 76.9 |
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. | 52.4 | 81.8 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 48.2 | 57.4 |
Pricing · per 1M tokens · projected $/mo at 10M tokens