Head-to-Head Model Comparison

Qwen3.5 Plus vs Gemini 3.1 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

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 Multimodale Nativa

Qwen3.5 Plus di Alibaba è un modello di IA progettato per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, con finestra di contesto da 1M, velocità di 85 token/s, indice di intelligenza di 87/100 e ta

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

Leader in Programmazione e Codice

Gemini 3.1 Pro di Google è un modello di IA progettato per l’ingegneria del software autonoma, il refactoring multi-file e il debug avanzato, con finestra di contesto da 1.0M, velocità di 110 token/s, indice di intelligenza di 86/100 e tari

Intelligence Index86 / 100

Input Token:

$2.00 / 1M

Output Token:

$12.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

74.5%

Differenze Chiave a Colpo d’Occhio

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 →

Feature	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

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Gemini 3.1 Pro

+10.5% SWE-bench lead

Cost

Qwen3.5 Plus

4.6x cheaper monthly runtime

Speed

Gemini 3.1 Pro

+29% faster generation

Context

Gemini 3.1 Pro

1.05M tokens window

Punteggi Benchmark Verificati

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

Latenza e Tempo di Risposta

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

Simulatore Interattivo dei Costi Token

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

Finestra di contesto da 1M con capacità massima di output fino a 16K token (SWE-bench Verified 64% · GPQA Diamond 72%)
Throughput elevato di 85 token/secondo con latenza al primo token (TTFT) di soli 490 ms
Economia API competitiva ($0.6/$2.4 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Gemini 3.1 Pro · Strengths & Key Advantages

Finestra di contesto da 1.0M con capacità massima di output fino a 66K token (SWE-bench Verified 74.5% · GPQA Diamond 86.5%)
Throughput elevato di 110 token/secondo con latenza al primo token (TTFT) di soli 780 ms
Economia API competitiva ($2/$12 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

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

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	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: Risposte Rapide (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.

Verdetto

Sia Qwen3.5 Plus (Ideale per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, sistemi RAG aziendali e integrazioni API scalabili.) sia Gemini 3.1 Pro (Ideale per l’ingegneria del software autonoma, il refactoring multi-file e il debug avanzato, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Qwen3.5 Plus guida nei benchmark di ragionamento e programmazione, Gemini 3.1 Pro garantisce una generazione più rapida e Qwen3.5 Plus offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Qwen3.5 Plus o Gemini 3.1 Pro?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Qwen3.5 Plus. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Qwen3.5 Plus e Gemini 3.1 Pro?+

Qwen3.5 Plus costa $0.60 / $2.40 per milione di token di input/output, mentre Gemini 3.1 Pro costa $2.00 / $12.00. Nel costo combinato, Qwen3.5 Plus risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Qwen3.5 Plus supporta 1M token di contesto contro 1.05M token di Gemini 3.1 Pro, mentre Gemini 3.1 Pro offre una velocità di generazione superiore.

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 e Confronta Qualsiasi Modello

Qwen3.5 Plus

Gemini 3.1 Pro

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Qwen3.5 Plus · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 3.1 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Qwen3.5 Plus vs Gemini 3.1 Pro: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

Related reading