Head-to-Head Model Comparison

Gemini 3 Pro vs GPT-5 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.

Gemini 3 ProProfile

GPT-5 ProProfile

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 Pro

Motore di Ragionamento Profondo

GPT-5 Pro di OpenAI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 400K, velocità di 55 token/s, indice di intelligenza di 62/100 e tariffa di $

Intelligence Index62 / 100

Input Token:

$15.00 / 1M

Output Token:

$120.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

78.5%

Differenze Chiave a Colpo d’Occhio

Gemini 3 Pro is 9.4x cheaper for API usage (input + output tokens combined).
Gemini 3 Pro has a larger context window (2M vs 400K tokens).
Gemini 3 Pro is faster at 118 tok/s vs 55 tok/s.
GPT-5 Pro leads on SWE-bench coding (78.5% vs 76.2%).

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

Feature	Gemini 3 Pro	GPT-5 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	62	62
Provider	Google	OpenAI
Input Price Cost per million input tokens	$2.00 / 1M	$15.00 / 1M
Output Price Cost per million output tokens	$12.00 / 1M	$120.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.74 / 1M	$16.05 / 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	272K
Throughput Speed Tokens generated per second	118 tok/s	55 tok/s
SWE-bench Verified Real-world software engineering	76.2%	78.5%
GPQA Diamond Graduate-level reasoning	73.5%	87.2%
Cached Input Price Prompt caching discount per 1M tokens	$0.20 / 1M	$1.50 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

GPT-5 Pro

+2.3% SWE-bench lead

Cost

Gemini 3 Pro

9.4x cheaper monthly runtime

Speed

Gemini 3 Pro

+115% 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 Pro

SWE-bench Verified (Autonomous Coding)

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

76.2%vs78.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

73.5%vs87.2%

MMLU-Pro (Multi-task Language Understanding)

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

86.8%vs88%

LMSYS Chatbot Arena Elo

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

1384ptsvs1374pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

12.9%vs14%

Terminal-Bench (Agentic Coding & Terminal Use)

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

47.9%vs51.5%

SciCode (Scientific Computing)

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

44.8%vs47%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs74.5%

AIME (Advanced Math Competition)

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

92.8%vs96%

Long-Context Reasoning

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

84.6%vs82.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

118 tok/s vs55 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 Pro4.20s

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

Gemini 3 Pro6.04s

GPT-5 Pro13.29s

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 Pro Monthly API Bill

$132.75 / month

$15/1M in · $120/1M out

Gemini 3 Pro saves approximately $118.65 / month (89%) under this workload.9.4x 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 Pro · Strengths & Key Advantages

Finestra di contesto da 400K con capacità massima di output fino a 272K token (SWE-bench Verified 78.5% · GPQA Diamond 87.2%)
Throughput elevato di 55 token/secondo con latenza al primo token (TTFT) di soli 4200 ms
Economia API competitiva ($15/$120 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 Pro	GPT-5 Pro
Cost per Task Estimated USD to finish one task	$2.40	$20.40
Output Tokens / Task Tokens generated per task	60K	72K
Reasoning Tokens / Task Thinking tokens burned per task	31K	48K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Gemini 3 Pro	GPT-5 Pro
Official API Model ID (SDK)	models/gemini-3-pro	gpt-5-pro
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	OpenAI Responses API & Chat Completions v1
Release Date	2025-11	2025-10
Knowledge Cutoff	January 2025	September 2024
Architecture	Sparse Multimodal MoE	Maximum-compute unified reasoning model
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 ($15/1M in) across full 400K window
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.2/1M with configurable TTL	Automatic prefix caching at $1.5/1M (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 Pro: Risposte Rapide (FAQ)

Which model is faster?

Gemini 3 Pro is faster, generating 118 tokens per second compared with 55 tokens per second.

Which model is cheaper to run?

Gemini 3 Pro is cheaper at $1.74 per 1M tokens blended, compared with $16.05 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 3 Pro has lower latency, with a time to first token of 1.80s compared with 4.20s.

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 Pro (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Gemini 3 Pro guida nei benchmark di ragionamento e programmazione, Gemini 3 Pro garantisce una generazione più rapida e Gemini 3 Pro 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 Pro?+

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 Pro?+

Gemini 3 Pro costa $2.00 / $12.00 per milione di token di input/output, mentre GPT-5 Pro costa $15.00 / $120.00. Nel costo combinato, Gemini 3 Pro 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 Pro, mentre Gemini 3 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 Pro vs GPT-5 Pro

Cambia e Confronta Qualsiasi Modello

Gemini 3 Pro

GPT-5 Pro

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 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Gemini 3 Pro vs GPT-5 Pro: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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