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Gemini 3.1 Pro vs KAT-Coder-Pro V2

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 KAT-Coder-Pro V2.

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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Kuaishou

KAT-Coder-Pro V2

KAT-Coder-Pro V2 is the latest high-performance model in KwaiKAT’s KAT-Coder series, designed for complex enterprise-grade software engineering and SaaS integration. It builds on the agentic coding strengths of earlier versions,...

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Technical Specifications

SpecificationGemini 3.1 ProKAT-Coder-Pro V2
ProviderGoogleKuaishou
Context Window2,000,000 tokens256,000 tokens
Agent Suitability93/100N/A
Time to First Token (TTFT)420 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202026-03-27

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro

$2.00

KAT-Coder-Pro V2

$0.30

Output Price per Million Tokens

Gemini 3.1 Pro

$12.00

KAT-Coder-Pro V2

$1.20

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
KAT-Coder-Pro V2
HumanEvalPython coding & logic synthesis
9460.0%vsN/A
Gemini 3.1 Pro
KAT-Coder-Pro V2
MATHComplex mathematical problem solving
8800.0%vsN/A
Gemini 3.1 Pro
KAT-Coder-Pro V2
GPQAGraduate-level expert reasoning
8130.0%vsN/A
Gemini 3.1 Pro
KAT-Coder-Pro V2
HellaSwagCommonsense reasoning and inference
9840.0%vsN/A
Gemini 3.1 Pro
KAT-Coder-Pro V2
MT-BenchMulti-turn conversation flow quality
950.0%vsN/A
Gemini 3.1 Pro
KAT-Coder-Pro V2

Gemini 3.1 Pro Quirks & Gotchas

  • Best model for massive context — 2M token window is class-leading
  • Tool calling requires explicit schema definition in Google AI Studio

KAT-Coder-Pro V2 Quirks & Gotchas

No developer gotchas reported.