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GPT-4.1 vs GLM 4.7 Flash

Detailed technical comparison between GPT-4.1 (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.

โšก Executive Summary & Verdict

Comparison Snapshot

GPT-4.1: 6 WinsvsGLM 4.7 Flash: 0 Wins
Context Leader

GPT-4.1

1,047,576 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-4.1

GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...

View GPT-4.1 Full Specs โ†’
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 โ†’

Technical Specifications

๐Ÿ† = Superior Spec
SpecificationGPT-4.1GLM 4.7 Flash
ProviderOpenAIZhipu AI
Context Window1,047,576 tokens๐Ÿ†202,752 tokens
Agent Suitability91/100N/A
Time to First Token (TTFT)250 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-04-142026-01-19

API Pricing Comparison

Input Price per Million Tokens

GPT-4.1

$2.00

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

GPT-4.1

$8.00

GLM 4.7 Flash

$0.40

๐Ÿ’ก Cost Ratio: GLM 4.7 Flash is 33.3x cheaper per input token than GPT-4.1.

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 (0โ€“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
81.0%vs77.2%+3.8% GPT-4.1
GPT-4.1 ๐Ÿ†
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
79.2%vs78.5%+0.7% GPT-4.1
GPT-4.1 ๐Ÿ†
GLM 4.7 Flash
MATHComplex mathematical problem solving
56.4%vs40.0%+16.4% GPT-4.1
GPT-4.1 ๐Ÿ†
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
38.4%vs31.0%+7.4% GPT-4.1
GPT-4.1 ๐Ÿ†
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
80.6%vs80.0%+0.6% GPT-4.1
GPT-4.1 ๐Ÿ†
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
8.7%vs8.1%+0.6% GPT-4.1
GPT-4.1 ๐Ÿ†
GLM 4.7 Flash

GPT-4.1 Quirks & Gotchas

  • โ–ธStrong tool-calling reliability โ€” good migration path from GPT-4o
  • โ–ธMigrate to GPT-5 for larger context window and improved reasoning

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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