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GPT-4o-mini (2024-07-18) vs GLM 5.2

Detailed technical comparison between GPT-4o-mini (2024-07-18) (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-mini (2024-07-18): 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

GPT-4o-mini (2024-07-18)

$0.15 / MTok
OpenAIactive

GPT-4o-mini (2024-07-18)

GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...

View GPT-4o-mini (2024-07-18) 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-mini (2024-07-18)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 Date2024-07-182026-06-16

API Pricing Comparison

Input Price per Million Tokens

GPT-4o-mini (2024-07-18)

$0.15

GLM 5.2

$0.80

Output Price per Million Tokens

GPT-4o-mini (2024-07-18)

$0.60

GLM 5.2

$2.52

💡 Cost Ratio: GPT-4o-mini (2024-07-18) is 5.3x cheaper per input token than GLM 5.2.

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
74.4%vs89.5%+15.1% GLM 5.2
GPT-4o-mini (2024-07-18)
GLM 5.2 🏆
HumanEvalPython coding & logic synthesis
70.6%vs91.2%+20.6% GLM 5.2
GPT-4o-mini (2024-07-18)
GLM 5.2 🏆
MATHComplex mathematical problem solving
43.8%vs80.5%+36.7% GLM 5.2
GPT-4o-mini (2024-07-18)
GLM 5.2 🏆
GPQAGraduate-level expert reasoning
31.2%vs53.5%+22.3% GLM 5.2
GPT-4o-mini (2024-07-18)
GLM 5.2 🏆
HellaSwagCommonsense reasoning and inference
78.4%vs89.8%+11.4% GLM 5.2
GPT-4o-mini (2024-07-18)
GLM 5.2 🏆
MT-BenchMulti-turn conversation flow quality
8.1%vs9.3%+1.2% GLM 5.2
GPT-4o-mini (2024-07-18)
GLM 5.2 🏆

GPT-4o-mini (2024-07-18) Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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