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Gemini 3.1 Pro vs GLM 4.5V

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 4.5V.

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 4.5V

GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...

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Technical Specifications

SpecificationGemini 3.1 ProGLM 4.5V
ProviderGoogleZhipu AI
Context Window2,000,000 tokens65,536 tokens
Agent Suitability93/100N/A
Time to First Token (TTFT)420 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202025-08-11

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro

$2.00

GLM 4.5V

$0.60

Output Price per Million Tokens

Gemini 3.1 Pro

$12.00

GLM 4.5V

$1.80

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%vsN/A
Gemini 3.1 Pro
GLM 4.5V
HumanEvalPython coding & logic synthesis
9460.0%vsN/A
Gemini 3.1 Pro
GLM 4.5V
MATHComplex mathematical problem solving
8800.0%vsN/A
Gemini 3.1 Pro
GLM 4.5V
GPQAGraduate-level expert reasoning
8130.0%vsN/A
Gemini 3.1 Pro
GLM 4.5V
HellaSwagCommonsense reasoning and inference
9840.0%vsN/A
Gemini 3.1 Pro
GLM 4.5V
MT-BenchMulti-turn conversation flow quality
950.0%vsN/A
Gemini 3.1 Pro
GLM 4.5V

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 4.5V Quirks & Gotchas

No developer gotchas reported.