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GPT-5 vs GLM 4.7 Flash

Detailed technical comparison between GPT-5 (OpenAI) and GLM 4.7 Flash (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 4.7 Flash: 0 Wins
Context Leader

GPT-5

400,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 4.7 Flash

$0.06 / 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 4.7 Flash

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...

View GLM 4.7 Flash Full Specs β†’

Technical Specifications

πŸ† = Superior Spec
SpecificationGPT-5GLM 4.7 Flash
ProviderOpenAIZhipu AI
Context Window400,000 tokensπŸ†202,752 tokens
Agent Suitability92/100 (est.)Not yet benchmarked
Time to First Token (TTFT)320 ms (est.)No public TTFT data
Deployment Modelmanaged apimanaged api
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2025-08-072026-01-19

API Pricing Comparison

Input Price per Million Tokens

GPT-5

$1.25

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

GPT-5

$10.00

GLM 4.7 Flash

$0.40

πŸ’‘ Cost Ratio: GLM 4.7 Flash is 20.8x 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%vs77.2%+14.9% GPT-5
GPT-5 πŸ†
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
94.0%vs78.5%+15.5% GPT-5
GPT-5 πŸ†
GLM 4.7 Flash
MATHComplex mathematical problem solving
89.5%vs40.0%+49.5% GPT-5
GPT-5 πŸ†
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
79.5%vs31.0%+48.5% GPT-5
GPT-5 πŸ†
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
98.5%vs80.0%+18.5% GPT-5
GPT-5 πŸ†
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
9.5%vs8.1%+1.4% GPT-5
GPT-5 πŸ†
GLM 4.7 Flash

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 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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