Head-to-Head Model Comparison

Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro

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 Flash-LiteProfile

Gemini 2.5 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 2.5 Flash-Lite

Modelo Ligero y Económico

Gemini 2.5 Flash-Lite de Google es un modelo de IA diseñado para máxima eficiencia de costos por token y alta velocidad en producción, con ventana de contexto de 1.0M, velocidad de 220 tokens/s, índice de inteligencia de 56/100 y tarifa de

Intelligence Index56 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Google

Gemini 2.5 Pro

Motor de Razonamiento Profundo

Gemini 2.5 Pro de Google es un modelo de IA diseñado para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, con ventana de contexto de 1.0M, velocidad de 95 tokens/s, índice de inteligencia de 78/100 y

Intelligence Index78 / 100

Input Token:

$1.25 / 1M

Output Token:

$10.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

63.8%

Diferencias Clave de un Vistazo

Gemini 2.5 Flash-Lite is 20.7x cheaper for API usage (input + output tokens combined).
Gemini 2.5 Flash-Lite is faster at 220 tok/s vs 95 tok/s.

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

Característica	Gemini 2.5 Flash-Lite	Gemini 2.5 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	56	78
Provider	Google	Google
Input Price Cost per million input tokens	$0.10 / 1M	$1.25 / 1M
Output Price Cost per million output tokens	$0.40 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.08 / 1M	$1.47 / 1M
Context Window Maximum input + output tokens	1.05M tokens~1,573 A4 pages of text	1.05M tokens~1,573 A4 pages of text
Max Output Tokens Per single request	33K	66K
Throughput Speed Tokens generated per second	220 tok/s	95 tok/s
SWE-bench Verified Real-world software engineering	N/A	63.8%
GPQA Diamond Graduate-level reasoning	N/A	84%
Cached Input Price Prompt caching discount per 1M tokens	$0.03 / 1M	$0.31 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Evaluations ongoing

Costo

Gemini 2.5 Flash-Lite

20.7x cheaper monthly runtime

Velocidad

Gemini 2.5 Flash-Lite

+132% faster generation

Contexto

Tied

1.05M tokens window

Puntuaciones de Benchmarks Verificadas

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

Gemini 2.5 Flash-LiteGemini 2.5 Pro

SWE-bench Verified (Autonomous Coding)

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

N/Avs63.8%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs84%

MMLU-Pro (Multi-task Language Understanding)

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

76.5%vs88.5%

LMSYS Chatbot Arena Elo

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

1330ptsvs1420pts

AIME (Advanced Math Competition)

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

N/Avs92%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

220 tok/s vs95 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 Flash-Lite0.32s

Gemini 2.5 Pro0.82s

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

Gemini 2.5 Flash-Lite2.59s

Gemini 2.5 Pro6.08s

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 Flash-Lite Monthly API Bill

$0.55 / month

$0.1/1M in · $0.4/1M out

Gemini 2.5 Pro Monthly API Bill

$11.34 / month

$1.25/1M in · $10/1M out

Gemini 2.5 Flash-Lite saves approximately $10.79 / month (95%) under this workload.20.7x Savings

Gemini 2.5 Flash-Lite · Strengths & Key Advantages

Ventana de contexto de 1.0M con hasta 33K tokens de salida máxima (MMLU-Pro 76.5% · Arena Elo 1330)
Rendimiento ágil de 220 tokens/segundo con latencia inicial (TTFT) de solo 320 ms
Economía de API competitiva ($0.1/$0.4 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 Pro · Strengths & Key Advantages

Ventana de contexto de 1.0M con hasta 66K tokens de salida máxima (SWE-bench Verified 63.8% · GPQA Diamond 84%)
Rendimiento ágil de 95 tokens/segundo con latencia inicial (TTFT) de solo 820 ms
Economía de API competitiva ($1.25/$10 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 Flash-Lite	Gemini 2.5 Pro
Cost per Task Estimated USD to finish one task	$0.35	$1.45
Output Tokens / Task Tokens generated per task	12K	45K
Reasoning Tokens / Task Thinking tokens burned per task	4K	22K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro: Respuestas Rápidas (FAQ)

Which is more intelligent, Gemini 2.5 Flash-Lite or Gemini 2.5 Pro?

Gemini 2.5 Pro is more intelligent. It scores 78 compared with 56 on the composite Intelligence Index.

Which model is faster?

Gemini 2.5 Flash-Lite is faster, generating 220 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

Gemini 2.5 Flash-Lite is cheaper at $0.08 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.5 Flash-Lite has lower latency, with a time to first token of 0.32s compared with 0.82s.

Veredicto

Tanto Gemini 2.5 Flash-Lite (Ideal para máxima eficiencia de costos por token y alta velocidad en producción, sistemas RAG empresariales y automatización mediante API.) como Gemini 2.5 Pro (Ideal para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Gemini 2.5 Pro lidera en inteligencia general y programación, Gemini 2.5 Flash-Lite ofrece mayor velocidad de generación de tokens y Gemini 2.5 Flash-Lite resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Gemini 2.5 Flash-Lite o Gemini 2.5 Pro?+

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

¿Cuánto cuesta la API de Gemini 2.5 Flash-Lite frente a Gemini 2.5 Pro?+

Gemini 2.5 Flash-Lite cuesta $0.10 / $0.40 por millón de tokens de entrada/salida, mientras que Gemini 2.5 Pro cuesta $1.25 / $10.00. En costo combinado, Gemini 2.5 Flash-Lite es la opción más económica.

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

Gemini 2.5 Flash-Lite cuenta con 1.05M tokens de contexto frente a 1.05M tokens de Gemini 2.5 Pro. En velocidad de inferencia, Gemini 2.5 Flash-Lite 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)

Característica	Gemini 2.5 Flash-Lite	Gemini 2.5 Pro
Official API Model ID (SDK)	models/gemini-2-5-flash-lite	models/gemini-2-5-pro
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-06	2025-03
Knowledge Cutoff	March 2025	January 2025
Architecture	Compact multimodal transformer with lightweight thinking	Pathways Multimodal Sparse Mixture-of-Experts with Thinking
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 $0.025/1M with configurable TTL	Implicit + Explicit Context Caching at $0.31/1M 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 Flash-Lite vs Gemini 2.5 Pro

Cambia y Compara Cualquier Modelo

Gemini 2.5 Flash-Lite

Gemini 2.5 Pro

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Gemini 2.5 Flash-Lite · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 2.5 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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