Head-to-Head Model Comparison

Gemini 3.1 Pro vs Claude Sonnet 4.5

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.

Gemini 3.1 ProProfile

Claude Sonnet 4.5Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

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%

Anthropic

Claude Sonnet 4.5

Modello Ammiraglia di Frontiera

Claude Sonnet 4.5 di Anthropic è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 1M, velocità di 90 token/s, indice di intelligenza di

Intelligence Index91 / 100

Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

77.8%

Differenze Chiave a Colpo d’Occhio

Gemini 3.1 Pro is 1.3x 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 90 tok/s.
Claude Sonnet 4.5 leads on SWE-bench coding (77.8% vs 74.5%).

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

Feature	Gemini 3.1 Pro	Claude Sonnet 4.5
Intelligence Index Composite reasoning & knowledge score (0-100)	86	91
Provider	Google	Anthropic
Input Price Cost per million input tokens	$2.00 / 1M	$3.00 / 1M
Output Price Cost per million output tokens	$12.00 / 1M	$15.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.95 / 1M	$2.31 / 1M
Context Window Maximum input + output tokens	1.05M tokens~1,573 A4 pages of text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	66K	64K
Throughput Speed Tokens generated per second	110 tok/s	90 tok/s
SWE-bench Verified Real-world software engineering	74.5%	77.8%
GPQA Diamond Graduate-level reasoning	86.5%	70.2%
Cached Input Price Prompt caching discount per 1M tokens	$0.50 / 1M	$0.30 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Claude Sonnet 4.5

+3.3% SWE-bench lead

Cost

Gemini 3.1 Pro

1.3x cheaper monthly runtime

Speed

Gemini 3.1 Pro

+22% faster generation

Context

Gemini 3.1 Pro

1.05M tokens window

Punteggi Benchmark Verificati

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

Gemini 3.1 ProClaude Sonnet 4.5

SWE-bench Verified (Autonomous Coding)

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

74.5%vs77.8%

GPQA Diamond (Doctorate-Level Science & Math)

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

86.5%vs70.2%

MMLU-Pro (Multi-task Language Understanding)

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

89.2%vs84.5%

LMSYS Chatbot Arena Elo

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

1475ptsvs1355pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs10.4%

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs50.1%

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs43.9%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs72.6%

AIME (Advanced Math Competition)

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

94%vs84.7%

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs74.8%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

110 tok/s vs90 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

Gemini 3.1 Pro0.78s

Claude Sonnet 4.50.90s

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

Gemini 3.1 Pro5.33s

Claude Sonnet 4.56.46s

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)

Gemini 3.1 Pro Monthly API Bill

$14.55 / month

$2/1M in · $12/1M out

Claude Sonnet 4.5 Monthly API Bill

$18.45 / month

$3/1M in · $15/1M out

Gemini 3.1 Pro saves approximately $3.90 / month (21%) under this workload.1.3x Savings

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

Claude Sonnet 4.5 · Strengths & Key Advantages

Finestra di contesto da 1M con capacità massima di output fino a 64K token (SWE-bench Verified 77.8% · GPQA Diamond 70.2%)
Throughput elevato di 90 token/secondo con latenza al primo token (TTFT) di soli 900 ms
Economia API competitiva ($3/$15 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	Gemini 3.1 Pro	Claude Sonnet 4.5
Cost per Task Estimated USD to finish one task	$1.85	$2.10
Output Tokens / Task Tokens generated per task	52K	55K
Reasoning Tokens / Task Thinking tokens burned per task	26K	30K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Gemini 3.1 Pro	Claude Sonnet 4.5
Official API Model ID (SDK)	models/gemini-3-1-pro	claude-sonnet-4-5-20251101
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2026-02	2025-11
Knowledge Cutoff	November 2025	March 2025
Architecture	Pathways High-Capacity Reasoning Architecture	Hybrid Reasoning
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 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 $0.5/1M with configurable TTL	$0.3/1M cached read (90% off); 5-min default & 1-hour extended 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	Native Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	Vertex AI Supervised Adapter Tuning & Context Distillation	Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
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	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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, audio, video	text, vision
Output Modalities	text	text

Gemini 3.1 Pro vs Claude Sonnet 4.5: Risposte Rapide (FAQ)

Which is more intelligent, Gemini 3.1 Pro or Claude Sonnet 4.5?

Claude Sonnet 4.5 is more intelligent. It scores 91 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 90 tokens per second.

Which model is cheaper to run?

Gemini 3.1 Pro is cheaper at $1.95 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 3.1 Pro has lower latency, with a time to first token of 0.78s compared with 0.90s.

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 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.) sia Claude Sonnet 4.5 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Claude Sonnet 4.5 guida nei benchmark di ragionamento e programmazione, Gemini 3.1 Pro garantisce una generazione più rapida e Gemini 3.1 Pro offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Gemini 3.1 Pro o Claude Sonnet 4.5?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Claude Sonnet 4.5. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Gemini 3.1 Pro e Claude Sonnet 4.5?+

Gemini 3.1 Pro costa $2.00 / $12.00 per milione di token di input/output, mentre Claude Sonnet 4.5 costa $3.00 / $15.00. Nel costo combinato, Gemini 3.1 Pro risulta più economico.

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

Gemini 3.1 Pro supporta 1.05M token di contesto contro 1M token di Claude Sonnet 4.5, 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)

Gemini 3.1 Pro vs Claude Sonnet 4.5

Cambia e Confronta Qualsiasi Modello

Gemini 3.1 Pro

Claude Sonnet 4.5

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Gemini 3.1 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Claude Sonnet 4.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Gemini 3.1 Pro vs Claude Sonnet 4.5: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

Related reading