Head-to-Head Model Comparison

Gemini 3 Flash vs Gemini 3 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial

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Gemini 3 FlashProfile

Gemini 3 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 3 Flash

Inferência Ultrarrápida

O Gemini 3 Flash da Google é um modelo de IA projetado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, oferecendo janela de contexto de 1.0M, velocidade de 180 tokens/s, índice de inteligência de 75/100 e t

Intelligence Index75 / 100

Input Token:

$0.50 / 1M

Output Token:

$3.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

66.5%

Google

Gemini 3 Pro

Modelo Principal de Fronteira

O Gemini 3 Pro da Google é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 2M, velocidade de 118 tokens/s, índice de inteligência de 62/100 e ta

Intelligence Index62 / 100

Input Token:

$2.00 / 1M

Output Token:

$12.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

76.2%

Principais Diferenças em Resumo

Gemini 3 Flash is 3.9x cheaper for API usage (input + output tokens combined).
Gemini 3 Pro has a larger context window (2M vs 1M tokens).
Gemini 3 Flash is faster at 180 tok/s vs 118 tok/s.
Gemini 3 Pro leads on SWE-bench coding (76.2% vs 66.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Gemini 3 Flash	Gemini 3 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	75	62
Provider	Google	Google
Input Price Cost per million input tokens	$0.50 / 1M	$2.00 / 1M
Output Price Cost per million output tokens	$3.00 / 1M	$12.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.49 / 1M	$1.74 / 1M
Context Window Maximum input + output tokens	1.05M tokens~1,573 A4 pages of text	2M tokens~3,000 A4 pages of text
Max Output Tokens Per single request	66K	66K
Throughput Speed Tokens generated per second	180 tok/s	118 tok/s
SWE-bench Verified Real-world software engineering	66.5%	76.2%
GPQA Diamond Graduate-level reasoning	79%	73.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.13 / 1M	$0.20 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Gemini 3 Pro

+9.7% SWE-bench lead

Cost

Gemini 3 Flash

3.9x cheaper monthly runtime

Speed

Gemini 3 Flash

+53% faster generation

Context

Gemini 3 Pro

2M tokens window

Pontuações de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

Gemini 3 FlashGemini 3 Pro

SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

66.5%vs76.2%

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

79%vs73.5%

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

85.8%vs86.8%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1425ptsvs1384pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs12.9%

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs47.9%

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs44.8%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs73%

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

88%vs92.8%

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs84.6%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

180 tok/s vs118 tok/s

Latência e Tempo de Resposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

Gemini 3 Flash0.40s

Gemini 3 Pro1.80s

Est. End-to-End Response (500 tokens)TTFT + generation time

Gemini 3 Flash3.18s

Gemini 3 Pro6.04s

Simulador Interativo de Custo de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Gemini 3 Flash Monthly API Bill

$3.64 / month

$0.5/1M in · $3/1M out

Gemini 3 Pro Monthly API Bill

$14.10 / month

$2/1M in · $12/1M out

Gemini 3 Flash saves approximately $10.46 / month (74%) under this workload.3.9x Savings

Gemini 3 Flash · Strengths & Key Advantages

Janela de contexto de 1.0M com limite máximo de saída de 66K tokens (SWE-bench Verified 66.5% · GPQA Diamond 79%)
Taxa de transferência rápida de 180 tokens/segundo com latência inicial (TTFT) de 400 ms
Economia de API competitiva ($0.5/$3 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Gemini 3 Pro · Strengths & Key Advantages

Janela de contexto de 2M com limite máximo de saída de 66K tokens (SWE-bench Verified 76.2% · GPQA Diamond 73.5%)
Taxa de transferência rápida de 118 tokens/segundo com latência inicial (TTFT) de 1800 ms
Economia de API competitiva ($2/$12 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	Gemini 3 Flash	Gemini 3 Pro
Cost per Task Estimated USD to finish one task	$0.95	$2.40
Output Tokens / Task Tokens generated per task	35K	60K
Reasoning Tokens / Task Thinking tokens burned per task	16K	31K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Gemini 3 Flash vs Gemini 3 Pro: Respostas Rápidas (FAQ)

Which is more intelligent, Gemini 3 Flash or Gemini 3 Pro?

Gemini 3 Flash is more intelligent. It scores 75 compared with 62 on the composite Intelligence Index.

Which model is faster?

Gemini 3 Flash is faster, generating 180 tokens per second compared with 118 tokens per second.

Which model is cheaper to run?

Gemini 3 Flash is cheaper at $0.49 per 1M tokens blended, compared with $1.74 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 3 Flash has lower latency, with a time to first token of 0.40s compared with 1.80s.

Which model has a larger context window?

Gemini 3 Pro has a larger context window, supporting 2M tokens compared with 1.05M tokens.

Veredito

Tanto Gemini 3 Flash (Indicado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, arquiteturas RAG corporativas e integração escalável via API.) quanto Gemini 3 Pro (Indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Gemini 3 Flash lidera em inteligência geral e programação, Gemini 3 Flash oferece geração mais rápida e Gemini 3 Flash apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Gemini 3 Flash ou Gemini 3 Pro?+

Nas avaliações de inteligência e código, Gemini 3 Flash leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Gemini 3 Flash ou Gemini 3 Pro?+

O Gemini 3 Flash custa $0.50 / $3.00 por 1M de tokens (entrada/saída) e o Gemini 3 Pro custa $2.00 / $12.00. No custo combinado, Gemini 3 Flash é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Gemini 3 Flash suporta 1.05M tokens de contexto contra 2M tokens do Gemini 3 Pro, enquanto Gemini 3 Flash entrega maior velocidade de geração.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Feature	Gemini 3 Flash	Gemini 3 Pro
Official API Model ID (SDK)	models/gemini-3-flash	models/gemini-3-pro
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-12	2025-11
Knowledge Cutoff	September 2025	January 2025
Architecture	Next-gen sparse multimodal mixture-of-experts	Sparse Multimodal MoE
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.125/1M with configurable TTL	Implicit + Explicit Context Caching at $0.2/1M with configurable TTL
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Built-in Google Search Grounding + Managed Python Code Execution Sandbox	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Vertex AI Supervised Adapter Tuning & Context Distillation	Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	Google DeepMind Frontier Safety Framework Verified	Google DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision, audio, video	text, vision, audio, video
Output Modalities	text	text

Gemini 3 Flash vs Gemini 3 Pro

Troque e Compare Qualquer Modelo

Gemini 3 Flash

Gemini 3 Pro

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Gemini 3 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 3 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Gemini 3 Flash vs Gemini 3 Pro: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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