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image model comparison

FLUX1.1 [pro] vs Gemini 3.1 Flash Lite Image

FLUX1.1 [pro] and Gemini 3.1 Flash Lite Image are both current image models, from Black Forest Labs and Google. Gemini 3.1 Flash Lite Image is 16% cheaper per image than FLUX1.1 [pro], $0.0336 vs $0.04. On Arena Text-to-Image, FLUX1.1 [pro] scores 1016 Elo and Gemini 3.1 Flash Lite Image 1250 Elo (Arena, measured October 7, 2026).

Data verified October 12, 2026 · Dataset 2026-10-12

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Side by side

Standard-tier prices in effect today. The better value in each row is highlighted.

FactFLUX1.1 [pro]Gemini 3.1 Flash Lite Image
Price per image$0.04$0.0336 (better)
Arena Text-to-Image1016 Elo (#9 of 9)1250 Elo (#6 of 9) (better)
Arena Image EditNot measured1314 Elo (#8 of 8)
ProviderBlack Forest LabsGoogle
Release dateNot reportedJune 30, 2026
AccessAPI onlyAPI only
Context windowNot reported65,536 tokens
Max outputNot reported4,096 tokens
Inputtexttext, image
Outputimagetext, image

Scores:Arena · 2026-10-12

Open both in the interactive comparison

When to choose each

FLUX1.1 [pro]

Best for

  • Hosted FLUX text-to-image generation

Watch out for

  • No exact compatible public benchmark snapshot is recorded
Full FLUX1.1 [pro] profile

Gemini 3.1 Flash Lite Image

Best for

  • Low-latency 1K image generation and edits

Watch out for

  • Only 1K output is supported; Google documents 2K and 4K as unsupported
Full Gemini 3.1 Flash Lite Image profile

FLUX1.1 [pro] vs Gemini 3.1 Flash Lite Image FAQ

Which is cheaper, FLUX1.1 [pro] or Gemini 3.1 Flash Lite Image?

Gemini 3.1 Flash Lite Image is 16% cheaper per image than FLUX1.1 [pro], $0.0336 vs $0.04.

Which scores higher on independent benchmarks, FLUX1.1 [pro] or Gemini 3.1 Flash Lite Image?

Gemini 3.1 Flash Lite Image leads on Arena Text-to-Image, 1250 Elo to 1016 Elo. Scores are independent evaluations, not either vendor's launch figures.

Production evaluation

Choosing between FLUX1.1 [pro] and Gemini 3.1 Flash Lite Image?

Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • A head-to-head evaluation on your real workload
  • Routing between models by cost and difficulty