Head-to-Head Model Comparison

Gemini 2.5 Computer Use vs Gemini 2.5 Flash

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Gemini 2.5 Computer Use vs Gemini 2.5 Flash: Benchmarks, Pricing & Speed Comparison

Gemini 2.5 Computer Use da Google e Gemini 2.5 Flash da Google são dois modelos de IA de destaque. O Gemini 2.5 Computer Use oferece uma janela de contexto de 128K tokens a $1.50/$8.00 por milhão de tokens, enquanto o Gemini 2.5 Flash oferece 1.05M tokens de contexto a $0.30/$2.50 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.

Comparação Direta (VS)

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Google

Gemini 2.5 Computer Use

IA Agêntica e Uso de Ferramentas

O Gemini 2.5 Computer Use da Google é um modelo de IA projetado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, oferecendo janela de contexto de 128K, velocidade de 85 tokens/s, índice de inteligência de 65/

Intelligence Index65 / 100
Input Token:

$1.50 / 1M

Output Token:

$8.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Google

Gemini 2.5 Flash

Inferência Ultrarrápida

O Gemini 2.5 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 160 tokens/s, índice de inteligência de 68/100 e

Intelligence Index68 / 100
Input Token:

$0.30 / 1M

Output Token:

$2.50 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

58.2%

Principais Diferenças em Resumo

  • Gemini 2.5 Flash is 3.6x cheaper for API usage (input + output tokens combined).
  • Gemini 2.5 Flash has a larger context window (1M vs 128K tokens).
  • Gemini 2.5 Flash is faster at 160 tok/s vs 85 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 2.5 Computer UseGemini 2.5 Flash
Intelligence Index
Composite reasoning & knowledge score (0-100)
6568
Provider
GoogleGoogle
Input Price
Cost per million input tokens
$1.50 / 1M$0.30 / 1M
Output Price
Cost per million output tokens
$8.00 / 1M$2.50 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.36 / 1M$0.36 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1.05M tokens~1,573 A4 pages of text
Max Output Tokens
Per single request
16K66K
Throughput Speed
Tokens generated per second
85 tok/s160 tok/s
SWE-bench Verified
Real-world software engineering
N/A58.2%
GPQA Diamond
Graduate-level reasoning
N/A75.4%
Cached Input Price
Prompt caching discount per 1M tokens
$0.38 / 1M$0.07 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini 2.5 Flash
3.6x cheaper monthly runtime
Speed
Gemini 2.5 Flash
+88% faster generation
Context
Gemini 2.5 Flash
1.05M tokens window

Pontuações de Benchmarks Verificadas

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

Gemini 2.5 Computer UseGemini 2.5 Flash
SWE-bench Verified (Autonomous Coding)

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

N/Avs58.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs75.4%
MMLU-Pro (Multi-task Language Understanding)

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

N/Avs83.2%
LMSYS Chatbot Arena Elo

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

1365ptsvs1385pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

45.2%vsN/A
AIME (Advanced Math Competition)

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

N/Avs84.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs160 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 2.5 Computer Use0.65s
Gemini 2.5 Flash0.45s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 2.5 Computer Use6.53s
Gemini 2.5 Flash3.58s

Simulador Interativo de Custo de Tokens

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

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Gemini 2.5 Computer Use Monthly API Bill
$10.01 / month
$1.5/1M in · $8/1M out
Gemini 2.5 Flash Monthly API Bill
$2.81 / month
$0.3/1M in · $2.5/1M out
Gemini 2.5 Flash saves approximately $7.20 / month (72%) under this workload.3.6x Savings

Gemini 2.5 Computer Use · Strengths & Key Advantages

  • Janela de contexto de 128K com limite máximo de saída de 16K tokens (Arena Elo 1365)
  • Taxa de transferência rápida de 85 tokens/segundo com latência inicial (TTFT) de 650 ms
  • Economia de API competitiva ($1.5/$8 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 2.5 Flash · Strengths & Key Advantages

  • Janela de contexto de 1.0M com limite máximo de saída de 66K tokens (SWE-bench Verified 58.2% · GPQA Diamond 75.4%)
  • Taxa de transferência rápida de 160 tokens/segundo com latência inicial (TTFT) de 450 ms
  • Economia de API competitiva ($0.3/$2.5 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

Token Use & Task Economics

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

MetricGemini 2.5 Computer UseGemini 2.5 Flash
Cost per Task
Estimated USD to finish one task
$1.15$0.85
Output Tokens / Task
Tokens generated per task
15K32K
Reasoning Tokens / Task
Thinking tokens burned per task
6K14K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 2.5 Computer UseGemini 2.5 Flash
Official API Model ID (SDK)models/gemini-2-5-computer-usemodels/gemini-2-5-flash
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-102025-06
Knowledge CutoffJune 2025March 2025
ArchitectureAction-grounded vision-language agent modelHigh-throughput sparse multimodal transformer with thinking mode
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1.5/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0.375/1M with configurable TTLImplicit + Explicit Context Caching at $0.075/1M with configurable TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationVertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)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 VRAMCloud-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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedGoogle DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision, audio, video
Output Modalitiestexttext

Gemini 2.5 Computer Use vs Gemini 2.5 Flash: Respostas Rápidas (FAQ)

Which is more intelligent, Gemini 2.5 Computer Use or Gemini 2.5 Flash?

Gemini 2.5 Flash is more intelligent. It scores 68 compared with 65 on the composite Intelligence Index.

Which model is faster?

Gemini 2.5 Flash is faster, generating 160 tokens per second compared with 85 tokens per second.

Which model is cheaper to run?

Gemini 2.5 Flash is cheaper at $0.36 per 1M tokens blended, compared with $1.36 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.5 Flash has lower latency, with a time to first token of 0.45s compared with 0.65s.

Which model has a larger context window?

Gemini 2.5 Flash has a larger context window, supporting 1.05M tokens compared with 128K tokens.

Veredito

Tanto Gemini 2.5 Computer Use (Indicado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, arquiteturas RAG corporativas e integração escalável via API.) quanto Gemini 2.5 Flash (Indicado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Gemini 2.5 Flash lidera em inteligência geral e programação, Gemini 2.5 Flash oferece geração mais rápida e Gemini 2.5 Flash apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Gemini 2.5 Computer Use ou Gemini 2.5 Flash?+

Nas avaliações de inteligência e código, Gemini 2.5 Flash leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Gemini 2.5 Computer Use ou Gemini 2.5 Flash?+

O Gemini 2.5 Computer Use custa $1.50 / $8.00 por 1M de tokens (entrada/saída) e o Gemini 2.5 Flash custa $0.30 / $2.50. No custo combinado, Gemini 2.5 Flash é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Gemini 2.5 Computer Use suporta 128K tokens de contexto contra 1.05M tokens do Gemini 2.5 Flash, enquanto Gemini 2.5 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.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fontes oficiais: Documentação oficial de API da Google e Google e benchmarks independentes (2026).