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GPT-4o (2024-05-13) vs GLM 5.2

Detailed technical comparison between GPT-4o (2024-05-13) (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.

โšก Executive Summary & Verdict

Comparison Snapshot

GPT-4o (2024-05-13): 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 (2024-05-13)

GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...

View GPT-4o (2024-05-13) Full Specs โ†’
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 โ†’

Technical Specifications

๐Ÿ† = Superior Spec
SpecificationGPT-4o (2024-05-13)GLM 5.2
ProviderOpenAIZhipu AI
Context Window128,000 tokens1,048,576 tokens๐Ÿ†
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2024-05-132026-06-16

API Pricing Comparison

Input Price per Million Tokens

GPT-4o (2024-05-13)

$5.00

GLM 5.2

$0.80

Output Price per Million Tokens

GPT-4o (2024-05-13)

$15.00

GLM 5.2

$2.50

๐Ÿ’ก Cost Ratio: GLM 5.2 is 6.3x cheaper per input token than GPT-4o (2024-05-13).

Want to test both models live?

Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Standardized Scores (0โ€“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
79.4%vs89.5%+10.1% GLM 5.2
GPT-4o (2024-05-13)
GLM 5.2 ๐Ÿ†
HumanEvalPython coding & logic synthesis
77.6%vs91.2%+13.6% GLM 5.2
GPT-4o (2024-05-13)
GLM 5.2 ๐Ÿ†
MATHComplex mathematical problem solving
54.8%vs80.5%+25.7% GLM 5.2
GPT-4o (2024-05-13)
GLM 5.2 ๐Ÿ†
GPQAGraduate-level expert reasoning
40.2%vs53.5%+13.3% GLM 5.2
GPT-4o (2024-05-13)
GLM 5.2 ๐Ÿ†
HellaSwagCommonsense reasoning and inference
82.4%vs89.8%+7.4% GLM 5.2
GPT-4o (2024-05-13)
GLM 5.2 ๐Ÿ†
MT-BenchMulti-turn conversation flow quality
8.5%vs9.3%+0.8% GLM 5.2
GPT-4o (2024-05-13)
GLM 5.2 ๐Ÿ†

GPT-4o (2024-05-13) Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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