Head-to-Head Model Comparison

Qwen3.5 Plus vs Gemini 3.1 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien

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Qwen3.5 PlusProfile

Gemini 3.1 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Alibaba

Qwen3.5 Plus

Nativ Multimodale KI

Qwen3.5 Plus von Alibaba ist ein KI-Modell für nativ multimodale Verarbeitung von Text und Bild sowie visuelle Dokumentenanalyse mit 1M Kontextfenster, 85 Token/s Durchsatz, einem Intelligenz-Index von 87/100 und $0.6/$2.4 pro 1M Token.

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

Spitzenmodell für Programmierung

Gemini 3.1 Pro von Google ist ein KI-Modell für autonomes Software-Engineering, Code-Refactoring und komplexe Fehleranalyse mit 1.0M Kontextfenster, 110 Token/s Durchsatz, einem Intelligenz-Index von 86/100 und $2/$12 pro 1M Token.

Intelligence Index86 / 100

Input Token:

$2.00 / 1M

Output Token:

$12.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

74.5%

Wichtigste Unterschiede auf einen Blick

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

Wer gewinnt in welcher Disziplin?

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

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Latenz & Antwortzeit

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

Interaktiver Token-Kosten-Simulator

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

1M Kontextfenster und bis zu 16K maximale Output-Token (SWE-bench Verified 64% · GPQA Diamond 72%)
Hohe Generierungsgeschwindigkeit von 85 Token/Sekunde bei nur 490 ms Erstlatenz (TTFT)
Effiziente API-Struktur ($0.6/$2.4 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe

Considerations & Trade-offs

Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Gemini 3.1 Pro · Strengths & Key Advantages

1.0M Kontextfenster und bis zu 66K maximale Output-Token (SWE-bench Verified 74.5% · GPQA Diamond 86.5%)
Hohe Generierungsgeschwindigkeit von 110 Token/Sekunde bei nur 780 ms Erstlatenz (TTFT)
Effiziente API-Struktur ($2/$12 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe

Considerations & Trade-offs

Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung

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

Technische Spezifikationen

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: Schnelle Antworten (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.

Fazit

Sowohl Qwen3.5 Plus (Optimal für nativ multimodale Verarbeitung von Text und Bild sowie visuelle Dokumentenanalyse, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Gemini 3.1 Pro (Optimal für autonomes Software-Engineering, Code-Refactoring und komplexe Fehleranalyse, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Qwen3.5 Plus führt bei komplexem Reasoning und Coding, Gemini 3.1 Pro liefert den höheren Token-Durchsatz und Qwen3.5 Plus ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Qwen3.5 Plus oder Gemini 3.1 Pro?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Qwen3.5 Plus vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Qwen3.5 Plus und Gemini 3.1 Pro?+

Qwen3.5 Plus kostet $0.60 / $2.40 pro 1M Input-/Output-Tokens, Gemini 3.1 Pro liegt bei $2.00 / $12.00. Beim gewichteten Gesamtpreis ist Qwen3.5 Plus günstiger.

Welches Modell hat das größere Kontextfenster und die höhere Geschwindigkeit?+

Qwen3.5 Plus bietet 1M Tokens Kontext gegenüber 1.05M Tokens bei Gemini 3.1 Pro. Bei der Generierungsgeschwindigkeit liegt Gemini 3.1 Pro vorn.

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

Beliebige Modelle wechseln & vergleichen

Qwen3.5 Plus

Gemini 3.1 Pro

Wer gewinnt in welcher Disziplin?

Geprüfte Benchmark-Ergebnisse im Vergleich

Latenz & Antwortzeit

Interaktiver Token-Kosten-Simulator

Qwen3.5 Plus · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 3.1 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Technische Spezifikationen

Qwen3.5 Plus vs Gemini 3.1 Pro: Schnelle Antworten (FAQ)

Fazit

Häufig gestellte Fragen (FAQ)

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