Head-to-Head Model Comparison

Gemini 2.5 Computer Use vs Gemini 2.5 Flash

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial

Cambia y Compara Cualquier Modelo

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Gemini 2.5 Computer UseProfile

Gemini 2.5 FlashProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 2.5 Computer Use

IA Agéntica y Uso de Herramientas

Gemini 2.5 Computer Use de Google es un modelo de IA diseñado para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, con ventana de contexto de 128K, velocidad de 85 tokens/s, índice de inteligencia de

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

Inferencia Ultrarrápida

Gemini 2.5 Flash de Google es un modelo de IA diseñado para interacción en tiempo real, baja latencia y enrutamiento de alto volumen, con ventana de contexto de 1.0M, velocidad de 160 tokens/s, índice de inteligencia de 68/100 y tarifa de $

Intelligence Index68 / 100

Input Token:

$0.30 / 1M

Output Token:

$2.50 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

58.2%

Diferencias Clave de un Vistazo

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 →

Característica	Gemini 2.5 Computer Use	Gemini 2.5 Flash
Intelligence Index Composite reasoning & knowledge score (0-100)	65	68
Provider	Google	Google
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 text	1.05M tokens~1,573 A4 pages of text
Max Output Tokens Per single request	16K	66K
Throughput Speed Tokens generated per second	85 tok/s	160 tok/s
SWE-bench Verified Real-world software engineering	N/A	58.2%
GPQA Diamond Graduate-level reasoning	N/A	75.4%
Cached Input Price Prompt caching discount per 1M tokens	$0.38 / 1M	$0.07 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Evaluations ongoing

Costo

Gemini 2.5 Flash

3.6x cheaper monthly runtime

Velocidad

Gemini 2.5 Flash

+88% faster generation

Contexto

Gemini 2.5 Flash

1.05M tokens window

Puntuaciones 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

Latencia y Tiempo de Respuesta

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 Interactivo de Costos 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 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

Ventana de contexto de 128K con hasta 16K tokens de salida máxima (Arena Elo 1365)
Rendimiento ágil de 85 tokens/segundo con latencia inicial (TTFT) de solo 650 ms
Economía de API competitiva ($1.5/$8 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Gemini 2.5 Flash · Strengths & Key Advantages

Ventana de contexto de 1.0M con hasta 66K tokens de salida máxima (SWE-bench Verified 58.2% · GPQA Diamond 75.4%)
Rendimiento ágil de 160 tokens/segundo con latencia inicial (TTFT) de solo 450 ms
Economía de API competitiva ($0.3/$2.5 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Token Use & Task Economics

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

Metric	Gemini 2.5 Computer Use	Gemini 2.5 Flash
Cost per Task Estimated USD to finish one task	$1.15	$0.85
Output Tokens / Task Tokens generated per task	15K	32K
Reasoning Tokens / Task Thinking tokens burned per task	6K	14K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	Gemini 2.5 Computer Use	Gemini 2.5 Flash
Official API Model ID (SDK)	models/gemini-2-5-computer-use	models/gemini-2-5-flash
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-10	2025-06
Knowledge Cutoff	June 2025	March 2025
Architecture	Action-grounded vision-language agent model	High-throughput sparse multimodal transformer with thinking mode
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 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 window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.375/1M with configurable TTL	Implicit + Explicit Context Caching at $0.075/1M 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)	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	text, vision, audio, video
Output Modalities	text	text

Gemini 2.5 Computer Use vs Gemini 2.5 Flash: Respuestas 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.

Veredicto

Tanto Gemini 2.5 Computer Use (Ideal para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, sistemas RAG empresariales y automatización mediante API.) como Gemini 2.5 Flash (Ideal para interacción en tiempo real, baja latencia y enrutamiento de alto volumen, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Gemini 2.5 Flash lidera en inteligencia general y programación, Gemini 2.5 Flash ofrece mayor velocidad de generación de tokens y Gemini 2.5 Flash resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Gemini 2.5 Computer Use o Gemini 2.5 Flash?+

En las pruebas de inteligencia compuesta y resolución de código, Gemini 2.5 Flash obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Gemini 2.5 Computer Use frente a Gemini 2.5 Flash?+

Gemini 2.5 Computer Use cuesta $1.50 / $8.00 por millón de tokens de entrada/salida, mientras que Gemini 2.5 Flash cuesta $0.30 / $2.50. En costo combinado, Gemini 2.5 Flash es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

Gemini 2.5 Computer Use cuenta con 128K tokens de contexto frente a 1.05M tokens de Gemini 2.5 Flash. En velocidad de inferencia, Gemini 2.5 Flash ofrece un rendimiento superior.

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)

Gemini 2.5 Computer Use vs Gemini 2.5 Flash

Cambia y Compara Cualquier Modelo

Gemini 2.5 Computer Use

Gemini 2.5 Flash

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Gemini 2.5 Computer Use · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 2.5 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

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

Veredicto

Preguntas frecuentes

Related reading