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GPT-4o vs GLM 4.7 Flash

Detailed technical comparison between GPT-4o (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-4o: 6 WinsvsGLM 4.7 Flash: 0 Wins
Context Leader

GLM 4.7 Flash

202,752 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-4o

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 Full Specs →
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 →

Technical Specifications

🏆 = Superior Spec
SpecificationGPT-4oGLM 4.7 Flash
ProviderOpenAIZhipu AI
Context Window128,000 tokens202,752 tokens🏆
Agent Suitability90/100 (est.)Not yet benchmarked
Time to First Token (TTFT)280 ms (est.)No public TTFT data
Deployment Modelmanaged apimanaged api
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2024-05-132026-01-19

API Pricing Comparison

Input Price per Million Tokens

GPT-4o

$2.50

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

GPT-4o

$10.00

GLM 4.7 Flash

$0.40

💡 Cost Ratio: GLM 4.7 Flash is 41.7x cheaper per input token than GPT-4o.

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.

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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
88.7%vs77.2%+11.5% GPT-4o
GPT-4o 🏆
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
90.2%vs78.5%+11.7% GPT-4o
GPT-4o 🏆
GLM 4.7 Flash
MATHComplex mathematical problem solving
76.6%vs40.0%+36.6% GPT-4o
GPT-4o 🏆
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
53.6%vs31.0%+22.6% GPT-4o
GPT-4o 🏆
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
88.7%vs80.0%+8.7% GPT-4o
GPT-4o 🏆
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
9.3%vs8.1%+1.2% GPT-4o
GPT-4o 🏆
GLM 4.7 Flash

GPT-4o Quirks & Gotchas

  • ▸Strong multimodal performance — best vision+tool calling combo
  • ▸Legacy model — migrate to GPT-5 for latest improvements

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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