LLM ReferenceLLM Reference

Gemini 2.0 Flash

gemini-2-0-flash

DeprecatedResearched 29d ago

Last refreshed 2026-05-11. Next refresh: weekly.

ProprietaryMultimodalCodingRAGAgentsLong contextVisionClassificationJSON / Tool use

Gemini 2.0 Flash is a legacy integration reference; keep it only while you identify a current replacement.

Decision context: Classification task fit, 3 tracked provider routes, and research from 2026-04-19.

Use it for

  • Teams maintaining an existing integration
  • Workloads that can use a 2M context window
  • Buyers comparing 3 tracked provider routes

Do not use it for

  • New production launches

Cheapest output

$0.400

GCP Vertex AI per 1M tokens

Provider routes

3

Tracked API hosts

Quality / dollar

Unknown

No output-token price in the ladder

Freshness

2026-04-19

Researched 29d ago

fresh

This API model is marked deprecated. Verify the replacement path before sending new production traffic.

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

Included by capability and metadata signals in the decision map.

Provider price ladder

ProviderInput / 1MOutput / 1MRoute
GCP Vertex AI$0.100$0.400
Serverless
Google AI Studio$0.100$0.400
Serverless
OpenRouter$0.100$0.400
Serverless

Benchmark peer barsfor Classification

Migration checks

No linked migration route is available for this model yet.

About

Google Gemini 2.0 Flash - lightweight, high-speed variant released January 2026. Optimized for cost and latency-sensitive applications.

Gemini 2.0 Flash has a 2M-token context window.

Gemini 2.0 Flash input tokens at $0.1/1M, output at $0.4/1M.

Capabilities

VisionMultimodalReasoningFunction CallingTool UseStructured OutputsCode Execution

Benchmark Scores(1)

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 PRO77.9https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro

Rankings

Specifications

Released2025-01-30
Context2M
Knowledge cutoff2025-04

Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website