Head-to-Head Model Comparison

GPT Image 1.5 vs Nano Banana 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.

GPT Image 1.5Profile

Nano Banana ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT Image 1.5

Generazione di Immagini IA

GPT Image 1.5 di OpenAI è un modello di IA progettato per la generazione di immagini IA ad alta risoluzione, il design visivo e il rendering tipografico, con finestra di contesto da 4K, velocità di 17 token/s, indice di intelligenza di 46/1

Intelligence Index46 / 100

Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

52%

Google

Nano Banana Pro

Generazione di Immagini IA

Nano Banana Pro di Google è un modello di IA progettato per la generazione di immagini IA ad alta risoluzione, il design visivo e il rendering tipografico, con finestra di contesto da 66K, velocità di 50 token/s, indice di intelligenza di 8

Intelligence Index83 / 100

Input Token:

$3.50 / 1M

Output Token:

$35.00 / 1M

Context Window:

65.5K tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

Nano Banana Pro is 1.1x cheaper for API usage (input + output tokens combined).
Nano Banana Pro has a larger context window (66K vs 4K tokens).
Nano Banana Pro is faster at 50 tok/s vs 17 tok/s.

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

Feature	GPT Image 1.5	Nano Banana Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	46	83
Provider	OpenAI	Google
Input Price Cost per million input tokens	$5.00 / 1M	$3.50 / 1M
Output Price Cost per million output tokens	$40.00 / 1M	$35.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$5.00 / 1M	$4.76 / 1M
Context Window Maximum input + output tokens	4.1K tokens~6 A4 pages of text	65.5K tokens~98 A4 pages of text
Max Output Tokens Per single request	4K	16K
Throughput Speed Tokens generated per second	17 tok/s	50 tok/s
SWE-bench Verified Real-world software engineering	52%	N/A
GPQA Diamond Graduate-level reasoning	66%	N/A
Cached Input Price Prompt caching discount per 1M tokens	$0.00 / 1M	$0.80 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Nano Banana Pro

1.1x cheaper monthly runtime

Speed

Nano Banana Pro

+194% faster generation

Context

Nano Banana Pro

65.5K tokens window

Punteggi Benchmark Verificati

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

GPT Image 1.5Nano Banana Pro

SWE-bench Verified (Autonomous Coding)

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

52%vsN/A

GPQA Diamond (Doctorate-Level Science & Math)

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

66%vsN/A

MMLU-Pro (Multi-task Language Understanding)

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

78.5%vsN/A

LMSYS Chatbot Arena Elo

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

1315ptsvs1415pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

9.2%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

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

30.5%vsN/A

SciCode (Scientific Computing)

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

32%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

56.5%vsN/A

AIME (Advanced Math Competition)

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

84%vsN/A

Long-Context Reasoning

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

68.5%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

17 tok/s vs50 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

GPT Image 1.57.10s

Nano Banana Pro1.20s

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

GPT Image 1.536.51s

Nano Banana Pro11.20s

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)

GPT Image 1.5 Monthly API Bill

$43.50 / month

$5/1M in · $40/1M out

Nano Banana Pro Monthly API Bill

$37.95 / month

$3.5/1M in · $35/1M out

Nano Banana Pro saves approximately $5.55 / month (13%) under this workload.1.1x Savings

GPT Image 1.5 · Strengths & Key Advantages

Finestra di contesto da 4K con capacità massima di output fino a 4K token (SWE-bench Verified 52% · GPQA Diamond 66%)
Throughput elevato di 17 token/secondo con latenza al primo token (TTFT) di soli 7100 ms
Economia API competitiva ($5/$40 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

Nano Banana Pro · Strengths & Key Advantages

Finestra di contesto da 66K con capacità massima di output fino a 16K token (Arena Elo 1415)
Throughput elevato di 50 token/secondo con latenza al primo token (TTFT) di soli 1200 ms
Economia API competitiva ($3.5/$35 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	GPT Image 1.5	Nano Banana Pro
Cost per Task Estimated USD to finish one task	$0.34	$0.05
Output Tokens / Task Tokens generated per task	9K	2K
Reasoning Tokens / Task Thinking tokens burned per task	0K	1K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	GPT Image 1.5	Nano Banana Pro
Official API Model ID (SDK)	gpt-image-1-5	models/nano-banana-pro
API Protocol	OpenAI Responses API & Chat Completions v1	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-11	2025-11
Knowledge Cutoff	October 2025	September 2025
Architecture	Native multimodal image generation transformer	High-fidelity design-grade image generation and compositional editor
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($5/1M in) across full 4K window	Flat rate ($3.5/1M in) across full 66K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0/1M (no extra cache-write fee)	Implicit + Explicit Context Caching at $0.8/1M 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	Prompt-based JSON extraction only	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	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)
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	OpenAI Preparedness Framework Audited & System Card Published	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
Output Modalities	image	image

GPT Image 1.5 vs Nano Banana Pro: Risposte Rapide (FAQ)

Which is more intelligent, GPT Image 1.5 or Nano Banana Pro?

Nano Banana Pro is more intelligent. It scores 83 compared with 46 on the composite Intelligence Index.

Which model is faster?

Nano Banana Pro is faster, generating 50 tokens per second compared with 17 tokens per second.

Which model is cheaper to run?

Nano Banana Pro is cheaper at $4.76 per 1M tokens blended, compared with $5.00 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nano Banana Pro has lower latency, with a time to first token of 1.20s compared with 7.10s.

Which model has a larger context window?

Nano Banana Pro has a larger context window, supporting 65.5K tokens compared with 4.1K tokens.

Verdetto

Sia GPT Image 1.5 (Ideale per la generazione di immagini IA ad alta risoluzione, il design visivo e il rendering tipografico, sistemi RAG aziendali e integrazioni API scalabili.) sia Nano Banana Pro (Ideale per la generazione di immagini IA ad alta risoluzione, il design visivo e il rendering tipografico, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Nano Banana Pro guida nei benchmark di ragionamento e programmazione, Nano Banana Pro garantisce una generazione più rapida e Nano Banana Pro offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, GPT Image 1.5 o Nano Banana Pro?+

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

Qual è la differenza di prezzo API tra GPT Image 1.5 e Nano Banana Pro?+

GPT Image 1.5 costa $5.00 / $40.00 per milione di token di input/output, mentre Nano Banana Pro costa $3.50 / $35.00. Nel costo combinato, Nano Banana Pro risulta più economico.

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

GPT Image 1.5 supporta 4.1K token di contesto contro 65.5K token di Nano Banana Pro, mentre Nano Banana 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)

GPT Image 1.5 vs Nano Banana Pro

Cambia e Confronta Qualsiasi Modello

GPT Image 1.5

Nano Banana Pro

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

GPT Image 1.5 · Strengths & Key Advantages

Considerations & Trade-offs

Nano Banana Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

GPT Image 1.5 vs Nano Banana Pro: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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