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GPT-5 vs GLM 5.2

Detailed technical comparison between GPT-5 (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-5: 6 WinsvsGLM 5.2: 0 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-5

GPT-5 is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy...

View GPT-5 Full Specs β†’
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 β†’

Technical Specifications

πŸ† = Superior Spec
SpecificationGPT-5GLM 5.2
ProviderOpenAIZhipu AI
Context Window400,000 tokens1,048,576 tokensπŸ†
Agent Suitability92/100N/A
Time to First Token (TTFT)320 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2025-08-072026-06-16

API Pricing Comparison

Input Price per Million Tokens

GPT-5

$1.25

GLM 5.2

$0.80

Output Price per Million Tokens

GPT-5

$10.00

GLM 5.2

$2.50

πŸ’‘ Cost Ratio: GLM 5.2 is 1.6x cheaper per input token than GPT-5.

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 (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
92.1%vs89.5%+2.6% GPT-5
GPT-5 πŸ†
GLM 5.2
HumanEvalPython coding & logic synthesis
94.0%vs91.2%+2.8% GPT-5
GPT-5 πŸ†
GLM 5.2
MATHComplex mathematical problem solving
89.5%vs80.5%+9.0% GPT-5
GPT-5 πŸ†
GLM 5.2
GPQAGraduate-level expert reasoning
79.5%vs53.5%+26.0% GPT-5
GPT-5 πŸ†
GLM 5.2
HellaSwagCommonsense reasoning and inference
98.5%vs89.8%+8.7% GPT-5
GPT-5 πŸ†
GLM 5.2
MT-BenchMulti-turn conversation flow quality
9.5%vs9.3%+0.2% GPT-5
GPT-5 πŸ†
GLM 5.2

GPT-5 Quirks & Gotchas

  • β–ΈReliable all-rounder β€” use as default for most production workflows
  • β–ΈNot recommended for advanced reasoning chains β€” use o3-mini instead

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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