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Gemini 3.1 Flash vs Gemini 3.5 Flash

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 Flash and Gemini 3.5 Flash.

Google

Gemini 3.1 Flash

Gemini 3.1 Flash is Google's high-speed, cost-efficient multimodal model in the 3.1 generation, purpose-built for high-volume content synthesis, classification, and intelligent routing at scale. Featuring a 1-million-token context window, it can process large batches of documents, customer data, or multimedia content in a single inference pass, dramatically reducing pipeline complexity. At just $0.25/MTok for input, it is one of the most affordable routes to Google-caliber multimodal AI, making it an ideal backbone for production pipelines, data enrichment workflows, and high-frequency API integrations.

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Google

Gemini 3.5 Flash

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...

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Technical Specifications

SpecificationGemini 3.1 FlashGemini 3.5 Flash
ProviderGoogleGoogle
Context Window1,000,000 tokens1,048,576 tokens
Agent Suitability86/10088/100
Time to First Token (TTFT)150 ms200 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202026-05-19

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Flash

$0.25

Gemini 3.5 Flash

$1.50

Output Price per Million Tokens

Gemini 3.1 Flash

$1.50

Gemini 3.5 Flash

$9.00

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
8680.0%vs9050.0%
Gemini 3.1 Flash
Gemini 3.5 Flash
HumanEvalPython coding & logic synthesis
8850.0%vs9210.0%
Gemini 3.1 Flash
Gemini 3.5 Flash
MATHComplex mathematical problem solving
7820.0%vs8500.0%
Gemini 3.1 Flash
Gemini 3.5 Flash
GPQAGraduate-level expert reasoning
6050.0%vs6820.0%
Gemini 3.1 Flash
Gemini 3.5 Flash
HellaSwagCommonsense reasoning and inference
9520.0%vs9780.0%
Gemini 3.1 Flash
Gemini 3.5 Flash
MT-BenchMulti-turn conversation flow quality
900.0%vs920.0%
Gemini 3.1 Flash
Gemini 3.5 Flash

Gemini 3.1 Flash Quirks & Gotchas

  • โ–ธMost cost-effective Google model โ€” ideal for high-volume pipelines
  • โ–ธContext caching available via Vertex AI for repeated document processing

Gemini 3.5 Flash Quirks & Gotchas

  • โ–ธExcellent multimodal performance โ€” native video understanding
  • โ–ธTool calling via Google's native function_declarations in Vertex AI