LLM ReferenceLLM Reference

Gemini 3 Flash

gemini-3-flash

Researched 1d ago

Last refreshed 2026-05-17. Next refresh: weekly.

ProprietaryMultimodalCodingRAGAgentsLong contextVisionClassificationJSON / Tool use

Gemini 3 Flash is worth evaluating for coding, rag, and agents when its provider route and context window match the workload.

Decision context: Agents task fit, 3 tracked provider routes, and research from 2026-05-17.

Use it for

  • Teams evaluating coding, rag, and agents
  • Workloads that can use a 1M context window
  • Buyers comparing 3 tracked provider routes

Do not use it for

  • Workloads where another current model has stronger sourced task evidence

Cheapest output

$3.00

GCP Vertex AI per 1M tokens

Provider routes

3

Tracked API hosts

Quality / dollar

Grade C

Ranked by benchmark score divided by cheapest output price

Freshness

2026-05-17

Researched 1d ago

fresh

Top use-case fit

Coding

Included by capability and metadata signals in the decision map.

RAG

Included by capability and metadata signals in the decision map.

Agents

Q/$ C

1 relevant benchmark in the decision map.

Provider price ladder

ProviderInput / 1MOutput / 1MRoute
GCP Vertex AI$0.500$3.00
Serverless
Google AI Studio$0.500$3.00
Serverless
Replicate API$0.500$3.00
Serverless

Benchmark peer barsfor Agents

Migration checks

No linked migration route is available for this model yet.

About

Gemini 3 Flash is Google's speed-optimized Gemini 3 model, available in public preview via the Gemini API and Vertex AI. It supports text, image, audio, and video inputs with a 1M token context window and is priced at $0.50 per 1M input tokens and $3.00 per 1M output tokens.

Gemini 3 Flash has a 1M-token context window.

Gemini 3 Flash input tokens at $0.5/1M, output at $3/1M.

Capabilities

VisionMultimodalFunction CallingTool UseCode ExecutionAudio

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.
BenchmarkScoreVersionSource
MMLU PRO88.6https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro
τ-bench71.5τ-benchhttps://taubench.com/
Chatbot Arena1467.0https://arena.ai/leaderboard

Rankings

Specifications

FamilyGemini 3
Released2025-12-17
Context1M
ArchitectureDecoder Only
Knowledge cutoff2025-01
Specializationgeneral
LicenseProprietary
Trainingpretrained

Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website