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Gemini 3.1 Pro vs GLM 4.7

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemini 3.1 Pro and GLM 4.7.

Google

Gemini 3.1 Pro

Google's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.

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Zhipu AI

GLM 4.7

GLM-4.7 is Z.aiโ€™s latest flagship model, featuring upgrades in two key areas: enhanced programming capabilities and more stable multi-step reasoning/execution. It demonstrates significant improvements in executing complex agent tasks while...

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Technical Specifications

SpecificationGemini 3.1 ProGLM 4.7
ProviderGoogleZhipu AI
Context Window2,000,000 tokens202,752 tokens
Agent Suitability93/100N/A
Time to First Token (TTFT)420 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202025-12-22

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro

$2.00

GLM 4.7

$0.40

Output Price per Million Tokens

Gemini 3.1 Pro

$12.00

GLM 4.7

$1.75

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9280.0%vs8150.0%
Gemini 3.1 Pro
GLM 4.7
HumanEvalPython coding & logic synthesis
9460.0%vs8200.0%
Gemini 3.1 Pro
GLM 4.7
MATHComplex mathematical problem solving
8800.0%vs5150.0%
Gemini 3.1 Pro
GLM 4.7
GPQAGraduate-level expert reasoning
8130.0%vs3800.0%
Gemini 3.1 Pro
GLM 4.7
HellaSwagCommonsense reasoning and inference
9840.0%vs8350.0%
Gemini 3.1 Pro
GLM 4.7
MT-BenchMulti-turn conversation flow quality
950.0%vs865.0%
Gemini 3.1 Pro
GLM 4.7

Gemini 3.1 Pro Quirks & Gotchas

  • โ–ธBest model for massive context โ€” 2M token window is class-leading
  • โ–ธTool calling requires explicit schema definition in Google AI Studio

GLM 4.7 Quirks & Gotchas

No developer gotchas reported.