Head-to-Head Model Comparison

Gemini 3 Pro vs GPT-5.1

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 ProProfile

GPT-5.1Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 3 Pro

Modello Ammiraglia di Frontiera

Gemini 3 Pro di Google 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 2M, velocità di 118 token/s, indice di intelligenza di 62/100

Intelligence Index62 / 100

Input Token:

$2.00 / 1M

Output Token:

$12.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

76.2%

OpenAI

GPT-5.1

Modello Ammiraglia di Frontiera

GPT-5.1 di OpenAI 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 400K, velocità di 130 token/s, indice di intelligenza di 60/100 e

Intelligence Index60 / 100

Input Token:

$1.25 / 1M

Output Token:

$10.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

74.9%

Differenze Chiave a Colpo d’Occhio

GPT-5.1 is 1.3x cheaper for API usage (input + output tokens combined).
Gemini 3 Pro has a larger context window (2M vs 400K tokens).
GPT-5.1 is faster at 130 tok/s vs 118 tok/s.
Gemini 3 Pro leads on SWE-bench coding (76.2% vs 74.9%).

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

Feature	Gemini 3 Pro	GPT-5.1
Intelligence Index Composite reasoning & knowledge score (0-100)	62	60
Provider	Google	OpenAI
Input Price Cost per million input tokens	$2.00 / 1M	$1.25 / 1M
Output Price Cost per million output tokens	$12.00 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.74 / 1M	$1.34 / 1M
Context Window Maximum input + output tokens	2M tokens~3,000 A4 pages of text	400K tokens~600 A4 pages of text
Max Output Tokens Per single request	66K	128K
Throughput Speed Tokens generated per second	118 tok/s	130 tok/s
SWE-bench Verified Real-world software engineering	76.2%	74.9%
GPQA Diamond Graduate-level reasoning	73.5%	72.1%
Cached Input Price Prompt caching discount per 1M tokens	$0.20 / 1M	$0.13 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Gemini 3 Pro

+1.3% SWE-bench lead

Cost

GPT-5.1

1.3x cheaper monthly runtime

Speed

GPT-5.1

+10% faster generation

Context

Gemini 3 Pro

2M tokens window

Punteggi Benchmark Verificati

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

Gemini 3 ProGPT-5.1

SWE-bench Verified (Autonomous Coding)

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

76.2%vs74.9%

GPQA Diamond (Doctorate-Level Science & Math)

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

73.5%vs72.1%

MMLU-Pro (Multi-task Language Understanding)

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

86.8%vs86.1%

LMSYS Chatbot Arena Elo

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

1384ptsvs1368pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

12.9%vs12.1%

Terminal-Bench (Agentic Coding & Terminal Use)

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

47.9%vs46.7%

SciCode (Scientific Computing)

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

44.8%vs43.2%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs71.8%

AIME (Advanced Math Competition)

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

92.8%vs91.2%

Long-Context Reasoning

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

84.6%vs77.9%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

118 tok/s vs130 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 Pro1.80s

GPT-5.11.20s

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

Gemini 3 Pro6.04s

GPT-5.15.05s

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 Pro Monthly API Bill

$14.10 / month

$2/1M in · $12/1M out

GPT-5.1 Monthly API Bill

$11.06 / month

$1.25/1M in · $10/1M out

GPT-5.1 saves approximately $3.04 / month (22%) under this workload.1.3x Savings

Gemini 3 Pro · Strengths & Key Advantages

Finestra di contesto da 2M con capacità massima di output fino a 66K token (SWE-bench Verified 76.2% · GPQA Diamond 73.5%)
Throughput elevato di 118 token/secondo con latenza al primo token (TTFT) di soli 1800 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

GPT-5.1 · Strengths & Key Advantages

Finestra di contesto da 400K con capacità massima di output fino a 128K token (SWE-bench Verified 74.9% · GPQA Diamond 72.1%)
Throughput elevato di 130 token/secondo con latenza al primo token (TTFT) di soli 1200 ms
Economia API competitiva ($1.25/$10 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

Token Use & Task Economics

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

Metric	Gemini 3 Pro	GPT-5.1
Cost per Task Estimated USD to finish one task	$2.40	$1.45
Output Tokens / Task Tokens generated per task	60K	52K
Reasoning Tokens / Task Thinking tokens burned per task	31K	28K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Gemini 3 Pro	GPT-5.1
Official API Model ID (SDK)	models/gemini-3-pro	gpt-5-1
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	OpenAI Responses API & Chat Completions v1
Release Date	2025-11	2025-11
Knowledge Cutoff	January 2025	October 2024
Architecture	Sparse Multimodal MoE	Unified Reasoning (Instant & 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) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens	Flat rate ($1.25/1M in) across full 400K window
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.2/1M with configurable TTL	Automatic prefix caching at $0.125/1M (no extra cache-write fee)
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 tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Vertex AI Supervised Adapter Tuning & Context Distillation	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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	OpenAI Preparedness Framework Audited & System Card Published
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 Pro vs GPT-5.1: Risposte Rapide (FAQ)

Which is more intelligent, Gemini 3 Pro or GPT-5.1?

Gemini 3 Pro is more intelligent. It scores 62 compared with 60 on the composite Intelligence Index.

Which model is faster?

GPT-5.1 is faster, generating 130 tokens per second compared with 118 tokens per second.

Which model is cheaper to run?

GPT-5.1 is cheaper at $1.34 per 1M tokens blended, compared with $1.74 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5.1 has lower latency, with a time to first token of 1.20s compared with 1.80s.

Which model has a larger context window?

Gemini 3 Pro has a larger context window, supporting 2M tokens compared with 400K tokens.

Verdetto

Sia Gemini 3 Pro (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) sia GPT-5.1 (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: Gemini 3 Pro guida nei benchmark di ragionamento e programmazione, GPT-5.1 garantisce una generazione più rapida e GPT-5.1 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Gemini 3 Pro o GPT-5.1?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Gemini 3 Pro. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Gemini 3 Pro e GPT-5.1?+

Gemini 3 Pro costa $2.00 / $12.00 per milione di token di input/output, mentre GPT-5.1 costa $1.25 / $10.00. Nel costo combinato, GPT-5.1 risulta più economico.

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

Gemini 3 Pro supporta 2M token di contesto contro 400K token di GPT-5.1, mentre GPT-5.1 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 Pro vs GPT-5.1

Cambia e Confronta Qualsiasi Modello

Gemini 3 Pro

GPT-5.1

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Gemini 3 Pro · Strengths & Key Advantages

Considerations & Trade-offs

GPT-5.1 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Gemini 3 Pro vs GPT-5.1: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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