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GPT-4o (2024-08-06) vs GLM 5.2

Detailed technical comparison between GPT-4o (2024-08-06) (OpenAI) and GLM 5.2 (Zhipu AI). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

⚡ Executive Summary & Verdict

Comparison Snapshot

GPT-4o (2024-08-06): 0 WinsvsGLM 5.2: 6 Wins
Context Leader

GLM 5.2

1,048,576 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 5.2

$0.80 / MTok
OpenAIactive

GPT-4o (2024-08-06)

The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format. Read more [here](https://openai.com/index/introducing-structured-outputs-in-the-api/). GPT-4o ("o" for "omni") is...

View GPT-4o (2024-08-06) Full Specs →
Zhipu AIactive

GLM 5.2

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

View GLM 5.2 Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationGPT-4o (2024-08-06)GLM 5.2
ProviderOpenAIZhipu AI
Context Window128,000 tokens1,048,576 tokens🏆
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2024-08-062026-06-16

API Pricing Comparison

Input Price per Million Tokens

GPT-4o (2024-08-06)

$2.50

GLM 5.2

$0.80

Output Price per Million Tokens

GPT-4o (2024-08-06)

$10.00

GLM 5.2

$2.50

💡 Cost Ratio: GLM 5.2 is 3.1x cheaper per input token than GPT-4o (2024-08-06).

Want to test both models live?

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Benchmark Performance Metrics

Standardized Scores (0–100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
80.4%vs89.5%+9.1% GLM 5.2
GPT-4o (2024-08-06)
GLM 5.2 🏆
HumanEvalPython coding & logic synthesis
78.6%vs91.2%+12.6% GLM 5.2
GPT-4o (2024-08-06)
GLM 5.2 🏆
MATHComplex mathematical problem solving
55.8%vs80.5%+24.7% GLM 5.2
GPT-4o (2024-08-06)
GLM 5.2 🏆
GPQAGraduate-level expert reasoning
41.2%vs53.5%+12.3% GLM 5.2
GPT-4o (2024-08-06)
GLM 5.2 🏆
HellaSwagCommonsense reasoning and inference
83.4%vs89.8%+6.4% GLM 5.2
GPT-4o (2024-08-06)
GLM 5.2 🏆
MT-BenchMulti-turn conversation flow quality
8.6%vs9.3%+0.7% GLM 5.2
GPT-4o (2024-08-06)
GLM 5.2 🏆

GPT-4o (2024-08-06) Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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