Head-to-Head Model Comparison

Qwen3.5 Plus vs Gemini 3.1 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.

Qwen3.5 PlusProfile

Gemini 3.1 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Alibaba

Qwen3.5 Plus

IA Multimodal Nativa

Qwen3.5 Plus de Alibaba es un modelo de IA diseñado para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, con ventana de contexto de 1M, velocidad de 85 tokens/s, índice de inteligencia de 87/100 y tarifa de

Intelligence Index87 / 100

Input Token:

$0.60 / 1M

Output Token:

$2.40 / 1M

Context Window:

1M tokens

SWE-bench Verified:

64%

Google

Gemini 3.1 Pro

Líder en Programación e Ingeniería

Gemini 3.1 Pro de Google es un modelo de IA diseñado para ingeniería de software autónoma, refactorización de código y depuración avanzada, con ventana de contexto de 1.0M, velocidad de 110 tokens/s, índice de inteligencia de 86/100 y tarif

Intelligence Index86 / 100

Input Token:

$2.00 / 1M

Output Token:

$12.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

74.5%

Diferencias Clave de un Vistazo

Qwen3.5 Plus is 4.6x cheaper for API usage (input + output tokens combined).
Gemini 3.1 Pro has a larger context window (1M vs 1M tokens).
Gemini 3.1 Pro is faster at 110 tok/s vs 85 tok/s.
Gemini 3.1 Pro leads on SWE-bench coding (74.5% vs 64.0%).

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

Característica	Qwen3.5 Plus	Gemini 3.1 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	87	86
Provider	Alibaba	Google
Input Price Cost per million input tokens	$0.60 / 1M	$2.00 / 1M
Output Price Cost per million output tokens	$2.40 / 1M	$12.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.40 / 1M	$1.95 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 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	110 tok/s
SWE-bench Verified Real-world software engineering	64%	74.5%
GPQA Diamond Graduate-level reasoning	72%	86.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.06 / 1M	$0.50 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Gemini 3.1 Pro

+10.5% SWE-bench lead

Costo

Qwen3.5 Plus

4.6x cheaper monthly runtime

Velocidad

Gemini 3.1 Pro

+29% faster generation

Contexto

Gemini 3.1 Pro

1.05M tokens window

Puntuaciones de Benchmarks Verificadas

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

Qwen3.5 PlusGemini 3.1 Pro

SWE-bench Verified (Autonomous Coding)

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

64%vs74.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

72%vs86.5%

MMLU-Pro (Multi-task Language Understanding)

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

85%vs89.2%

LMSYS Chatbot Arena Elo

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

1410ptsvs1475pts

AIME (Advanced Math Competition)

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

N/Avs94%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs110 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

Qwen3.5 Plus0.49s

Gemini 3.1 Pro0.78s

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

Qwen3.5 Plus6.37s

Gemini 3.1 Pro5.33s

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)

Qwen3.5 Plus Monthly API Bill

$3.15 / month

$0.6/1M in · $2.4/1M out

Gemini 3.1 Pro Monthly API Bill

$14.55 / month

$2/1M in · $12/1M out

Qwen3.5 Plus saves approximately $11.40 / month (78%) under this workload.4.6x Savings

Qwen3.5 Plus · Strengths & Key Advantages

Ventana de contexto de 1M con hasta 16K tokens de salida máxima (SWE-bench Verified 64% · GPQA Diamond 72%)
Rendimiento ágil de 85 tokens/segundo con latencia inicial (TTFT) de solo 490 ms
Economía de API competitiva ($0.6/$2.4 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 3.1 Pro · Strengths & Key Advantages

Ventana de contexto de 1.0M con hasta 66K tokens de salida máxima (SWE-bench Verified 74.5% · GPQA Diamond 86.5%)
Rendimiento ágil de 110 tokens/segundo con latencia inicial (TTFT) de solo 780 ms
Economía de API competitiva ($2/$12 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 volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos

Token Use & Task Economics

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

Metric	Qwen3.5 Plus	Gemini 3.1 Pro
Cost per Task Estimated USD to finish one task	$0.19	$1.85
Output Tokens / Task Tokens generated per task	24K	52K
Reasoning Tokens / Task Thinking tokens burned per task	8K	26K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	Qwen3.5 Plus	Gemini 3.1 Pro
Official API Model ID (SDK)	qwen3-5-plus-instruct	models/gemini-3-1-pro
API Protocol	Alibaba REST API (OpenAI-Compatible)	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2026-02	2026-02
Knowledge Cutoff	December 2025	November 2025
Architecture	Enterprise Million-Token Multimodal Transformer	Pathways High-Capacity Reasoning Architecture
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 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)	Flat rate ($0.6/1M in) across full 1000K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Cached input at $0.06/1M tokens	Implicit + Explicit Context Caching at $0.5/1M 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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	API Prompt Engineering & RAG 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	Alibaba Production Safety & Alignment 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

Qwen3.5 Plus vs Gemini 3.1 Pro: Respuestas Rápidas (FAQ)

Which is more intelligent, Qwen3.5 Plus or Gemini 3.1 Pro?

Qwen3.5 Plus is more intelligent. It scores 87 compared with 86 on the composite Intelligence Index.

Which model is faster?

Gemini 3.1 Pro is faster, generating 110 tokens per second compared with 85 tokens per second.

Which model is cheaper to run?

Qwen3.5 Plus is cheaper at $0.40 per 1M tokens blended, compared with $1.95 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3.5 Plus has lower latency, with a time to first token of 0.49s compared with 0.78s.

Which model has a larger context window?

Gemini 3.1 Pro has a larger context window, supporting 1.05M tokens compared with 1M tokens.

Veredicto

Tanto Qwen3.5 Plus (Ideal para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, sistemas RAG empresariales y automatización mediante API.) como Gemini 3.1 Pro (Ideal para ingeniería de software autónoma, refactorización de código y depuración avanzada, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Qwen3.5 Plus lidera en inteligencia general y programación, Gemini 3.1 Pro ofrece mayor velocidad de generación de tokens y Qwen3.5 Plus resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Qwen3.5 Plus o Gemini 3.1 Pro?+

En las pruebas de inteligencia compuesta y resolución de código, Qwen3.5 Plus obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Qwen3.5 Plus frente a Gemini 3.1 Pro?+

Qwen3.5 Plus cuesta $0.60 / $2.40 por millón de tokens de entrada/salida, mientras que Gemini 3.1 Pro cuesta $2.00 / $12.00. En costo combinado, Qwen3.5 Plus es la opción más económica.

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

Qwen3.5 Plus cuenta con 1M tokens de contexto frente a 1.05M tokens de Gemini 3.1 Pro. En velocidad de inferencia, Gemini 3.1 Pro 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)

Qwen3.5 Plus vs Gemini 3.1 Pro

Cambia y Compara Cualquier Modelo

Qwen3.5 Plus

Gemini 3.1 Pro

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Qwen3.5 Plus · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 3.1 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Qwen3.5 Plus vs Gemini 3.1 Pro: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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