Gemini 3.1 Flash Lite is Google’s GA high-efficiency multimodal model optimized for low-latency, high-volume workloads.
- Context window: 1,048,576 tokens
- Input: text, image, video, file, audio
- Output: text
- Pricing: $0.25/M input tokens, $1.5/M output tokens
Community sentiment
Negative (-32) — 3 positive, 5 negative, 6 neutral across 14 community samples from X and the web, as of 2026-10-02.
Community discussion is mixed: users praise Gemini 3.1 Flash Lite for very low latency and some benchmark wins, but many posts criticize inconsistent answer rates, privacy/data leakage in raw mode, and poor cost-efficiency versus cheaper models. Concerns also include degraded performance on certain benchmarks and limitations for agentic/video tasks.
- “@luke_pighetti I'm getting only 3.82 latency in total. I'm using gemini-3.1-flash-lite https://t.co/TRpfoCHLJl” — X
- “three low-cost AI models for API use right now ↓ standard price per 1m text tokens (input / output): • Ministral 3 3B — $0.10 / $0.10 • GPT-6 Luna — $0.10 / $0.50 • Gemini 3.1 Flash-Lite — $0.25 / $1.50 for tagging, extraction or short summaries i'd try a cheaper model first and” — X
- “4/ In Raw mode (reasoning off), gemini-3.1-flash-lite leaked 14 times, via JSON dumps, translation, rot13, spelling out and the injected email. With SERV's reasoning layer on, leaks fell to 1. My personal guess is that SERV rewrites the prompt with a stricter privacy rule.” — X
- “Ultimate Gemini Model Comparison 2026: 2.5 to Gemini 4 - Fello AI — 12 hours ago · Gemini 3.1 Flash-Lite. Long coding, knowledge-work and cyber-defense tasks … it notably beat 3.1 Pro on several coding and agentic benchmarks despite being a ...” — the web
View on OpenRouter.
Model data sourced from OpenRouter.