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GLM 5 vs GPT-5

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for GLM 5 and GPT-5.

Zhipu AI

GLM 5

GLM-5 is Z.ai’s flagship open-source foundation model engineered for complex systems design and long-horizon agent workflows. Built for expert developers, it delivers production-grade performance on large-scale programming tasks, rivaling leading...

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OpenAI

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...

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Technical Specifications

SpecificationGLM 5GPT-5
ProviderZhipu AIOpenAI
Context Window202,752 tokens400,000 tokens
Agent SuitabilityN/A92/100
Time to First Token (TTFT)N/A320 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-02-112025-08-07

API Pricing Comparison

Input Price per Million Tokens

GLM 5

$0.60

GPT-5

$1.25

Output Price per Million Tokens

GLM 5

$1.92

GPT-5

$10.00

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8650.0%vs9210.0%
GLM 5
GPT-5
HumanEvalPython coding & logic synthesis
8700.0%vs9400.0%
GLM 5
GPT-5
MATHComplex mathematical problem solving
7400.0%vs8950.0%
GLM 5
GPT-5
GPQAGraduate-level expert reasoning
4800.0%vs7950.0%
GLM 5
GPT-5
HellaSwagCommonsense reasoning and inference
8700.0%vs9850.0%
GLM 5
GPT-5
MT-BenchMulti-turn conversation flow quality
910.0%vs950.0%
GLM 5
GPT-5

GLM 5 Quirks & Gotchas

No developer gotchas reported.

GPT-5 Quirks & Gotchas

  • Reliable all-rounder — use as default for most production workflows
  • Not recommended for advanced reasoning chains — use o3-mini instead