Gemini 3.1 Flash-Lite

Name: Gemini 3.1 Flash-Lite
Author: Google DeepMind

Released

2026-05-07

Last refreshed

2026-06-29

Status

Researched 77d ago

ProprietaryCommercial use: conditionalMultimodalCodingRAGAgentsLong contextVisionJSON / Tool use

Gemini 3.1 Flash-Lite is worth evaluating for coding, rag, and agents when its provider route and context window match the workload.

Use it for

Teams evaluating coding, rag, and agents
Workloads that can use a 1.05m context window
Buyers comparing 3 tracked provider routes

Do not use it for

Workloads where another current model has stronger sourced task evidence

Specifications

Family: Gemini 3.1
Released: 2026-05-07
Context: 1.05m
Max output: 66,000
Architecture: Decoder Only
Knowledge cutoff: 2025-01
Specialization: general
Openness: Proprietary
License: ProprietaryCommercial use: conditional
Weights: Not released
Code: Unknown
Training: Pretrained

Created by

Google DeepMind

Pioneering artificial intelligence research.

London, United Kingdom

Founded 2014

Website

Pricing

Output / 1M

$1.50

Input / 1M

$0.250

Cheapest of 3 routes · Google AI Studio

Providers(3)

Google AI Studio OpenRouter Vercel AI Gateway

View 3 provider routes

Links

Website

About

Gemini 3.1 Flash-Lite is Google's generally available low-latency Gemini 3.1 model, launched May 7, 2026. It is optimized for high-volume, cost-sensitive workloads with text, image, and video inputs, a 1M token context window, and a 66K token maximum output. The GA model uses the stable API ID gemini-3.1-flash-lite and replaces gemini-3.1-flash-lite-preview, which is scheduled to shut down on May 25, 2026. Pricing is $0.25 per 1M input tokens and $1.50 per 1M output tokens.

Top use-case fit: coding, agents, and build tasks

Coding

Included by capability and metadata signals in the decision map.

RAG

Included by capability and metadata signals in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Provider price ladder

Compare all 3

Compare API pricing across 3 providers for input and output tokens, batch, and cached reads when available.

Provider	Input / 1M	Output / 1M	Cache	Route
Google AI Studio	$0.250	$1.50	-	Serverless
OpenRouter	$0.250	$1.50	-	Serverless
Vercel AI Gateway	$0.250	$1.50	read $0.030	Serverless

Available via routers & gateways(13)

LiteLLM

Gateway

Open-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.

Free OSSGoogle AI Studio

OpenRouter

Hybrid

Unified hybrid gateway to 400+ models from 60+ providers via a single OpenAI-compatible API, with optional auto-routing that selects the best model per prompt.

PassthroughGoogle AI Studio

Portkey

Gateway

Production AI gateway routing to 1,600+ LLMs with failover, load balancing, semantic caching, and guardrails; Apache 2.0 core is fully self-hostable with the complete feature set.

SubscriptionGoogle AI Studio

AIRouter

Router

Commercial LLM router that analyzes incoming requests and routes to the optimal model for cost/quality/latency via a drop-in OpenAI-compatible API, with a privacy-preserving embedding mode that avoids sending prompt content.

Passthrough + feeGoogle AI Studio

Helicone

Gateway

Observability-first AI gateway with routing, caching, rate limiting, and request tracing; Apache 2.0 open-source core with a managed hosted tier for logging and analytics.

SubscriptionGoogle AI Studio

Kong AI Gateway

Gateway

Multi-LLM AI gateway built on Kong Gateway 3.x, adding semantic routing, load balancing, guardrails, and MCP traffic analytics as plugins over Kong's existing API management platform.

SubscriptionGoogle AI Studio

Capabilities

VisionMultimodalJSON / Tool useStructured OutputsCode Execution

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Benchmark scores(3)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.

Benchmark	Score	Version	Evaluation	Source
MMMU Pro	76.8	LLM-Stats aggregatorObserved 2026-06-07	—	Source
Google-Proof Q&A	86.9	diamondObserved 2026-05-12	—	Source
Chatbot Arena	1432.0	Arena EloObserved 2026-05-12	—	Source