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GPT-4o (2024-08-06) vs GLM 4.7 Flash

Detailed technical comparison between GPT-4o (2024-08-06) (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 (2024-08-06): 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 (2024-08-06)

The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format. Read more [here](https://openai.com/index/introducing-structured-outputs-in-the-api/). GPT-4o ("o" for "omni") is...

View GPT-4o (2024-08-06) 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-4o (2024-08-06)GLM 4.7 Flash
ProviderOpenAIZhipu AI
Context Window128,000 tokens202,752 tokens🏆
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-08-062026-01-19

API Pricing Comparison

Input Price per Million Tokens

GPT-4o (2024-08-06)

$2.50

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

GPT-4o (2024-08-06)

$10.00

GLM 4.7 Flash

$0.40

💡 Cost Ratio: GLM 4.7 Flash is 41.7x cheaper per input token than GPT-4o (2024-08-06).

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
80.4%vs77.2%+3.2% GPT-4o (2024-08-06)
GPT-4o (2024-08-06) 🏆
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
78.6%vs78.5%+0.1% GPT-4o (2024-08-06)
GPT-4o (2024-08-06) 🏆
GLM 4.7 Flash
MATHComplex mathematical problem solving
55.8%vs40.0%+15.8% GPT-4o (2024-08-06)
GPT-4o (2024-08-06) 🏆
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
41.2%vs31.0%+10.2% GPT-4o (2024-08-06)
GPT-4o (2024-08-06) 🏆
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
83.4%vs80.0%+3.4% GPT-4o (2024-08-06)
GPT-4o (2024-08-06) 🏆
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
8.6%vs8.1%+0.5% GPT-4o (2024-08-06)
GPT-4o (2024-08-06) 🏆
GLM 4.7 Flash

GPT-4o (2024-08-06) Quirks & Gotchas

No developer gotchas reported.

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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