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Gemini 3.6 Flash vs GLM 5.2

Detailed technical comparison between Gemini 3.6 Flash (Google) and GLM 5.2 (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

Gemini 3.6 Flash: 0 WinsvsGLM 5.2: 6 Wins
Context Leader

Tie

Equal Capacity
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 5.2

$0.80 / MTok
Googleactive

Gemini 3.6 Flash

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and...

View Gemini 3.6 Flash Full Specs →
Zhipu AIactive

GLM 5.2

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

View GLM 5.2 Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationGemini 3.6 FlashGLM 5.2
ProviderGoogleZhipu AI
Context Window1,048,576 tokens1,048,576 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitybetabeta
API AvailableYesYes
Released Date2026-07-212026-06-16

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.6 Flash

$1.50

GLM 5.2

$0.80

Output Price per Million Tokens

Gemini 3.6 Flash

$7.50

GLM 5.2

$2.52

💡 Cost Ratio: GLM 5.2 is 1.9x cheaper per input token than Gemini 3.6 Flash.

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
73.6%vs89.5%+15.9% GLM 5.2
Gemini 3.6 Flash
GLM 5.2 🏆
HumanEvalPython coding & logic synthesis
69.8%vs91.2%+21.4% GLM 5.2
Gemini 3.6 Flash
GLM 5.2 🏆
MATHComplex mathematical problem solving
43.0%vs80.5%+37.5% GLM 5.2
Gemini 3.6 Flash
GLM 5.2 🏆
GPQAGraduate-level expert reasoning
30.4%vs53.5%+23.1% GLM 5.2
Gemini 3.6 Flash
GLM 5.2 🏆
HellaSwagCommonsense reasoning and inference
77.6%vs89.8%+12.2% GLM 5.2
Gemini 3.6 Flash
GLM 5.2 🏆
MT-BenchMulti-turn conversation flow quality
8.0%vs9.3%+1.3% GLM 5.2
Gemini 3.6 Flash
GLM 5.2 🏆

Gemini 3.6 Flash Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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