GoogleGemini 3.1 ProVSGoogleGemini 3.5 Flash Lite

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

This matchup represents a clear tradeoff between peak intelligence and budget efficiency. Gemini 3.1 Pro is noticeably superior (holding a 5.1% average lead in benchmarks), but it carries a massive 5.3x price premium. Choose Gemini 3.1 Pro if you need top-tier reasoning or code debugging, but for high-volume pipelines, Gemini 3.5 Flash Lite is the smarter business decision.

Was this recommendation helpful?

Model Specs

Gemini 3.1 Pro

Website

Benchmarks & Scores

Coding (swe-bench-pro)

54.2%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)Winner (+10.3%)

94.3%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)

$4.50Input: $2.00 | Output: $12.00

Context Window

1.05M tokens

Model Specs

Gemini 3.5 Flash Lite

Website

Benchmarks & Scores

Coding (swe-bench-pro)

54.2%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)

84%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)5.3x cheaper

$0.85Input: $0.30 | Output: $2.50

Context Window

1.05M tokens

Read our data collection methodology

Frequently Asked Questions about Gemini 3.1 Pro vs Gemini 3.5 Flash Lite

Gemini 3.5 Flash Lite is cheaper than Gemini 3.1 Pro. Gemini 3.5 Flash Lite has a blended cost of $0.85/1M tokens, which is about 5.3x cheaper than Gemini 3.1 Pro at $4.50/1M tokens.

Both Gemini 3.1 Pro and Gemini 3.5 Flash Lite score identically at 54.2% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases).

Related Matchups

Explore similar comparisons for Gemini 3.1 Pro and Gemini 3.5 Flash Lite.

Browse More Comparisons

GoogleGemini 3.1 Pro

OpenAIGPT-5.5

Compare Specs

GoogleGemini 3.5 Flash Lite

Do you want to find a model for your constraints?

Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.

Open Model Finder