Head-to-Head Model Comparison

Nano Banana vs GPT Image 1.5

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.

Nano BananaProfile

GPT Image 1.5Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Nano Banana

Generazione di Immagini IA

Nano Banana 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 33K, velocità di 60 token/s, indice di intelligenza di 75/10

Intelligence Index75 / 100

Input Token:

$2.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

N/A

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%

Differenze Chiave a Colpo d’Occhio

Nano Banana is 2.0x cheaper for API usage (input + output tokens combined).
Nano Banana has a larger context window (33K vs 4K tokens).
Nano Banana is faster at 60 tok/s vs 17 tok/s.

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

Feature	Nano Banana	GPT Image 1.5
Intelligence Index Composite reasoning & knowledge score (0-100)	75	46
Provider	Google	OpenAI
Input Price Cost per million input tokens	$2.00 / 1M	$5.00 / 1M
Output Price Cost per million output tokens	$20.00 / 1M	$40.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.75 / 1M	$5.00 / 1M
Context Window Maximum input + output tokens	32.8K tokens~49 A4 pages of text	4.1K tokens~6 A4 pages of text
Max Output Tokens Per single request	8K	4K
Throughput Speed Tokens generated per second	60 tok/s	17 tok/s
SWE-bench Verified Real-world software engineering	N/A	52%
GPQA Diamond Graduate-level reasoning	N/A	66%
Cached Input Price Prompt caching discount per 1M tokens	$0.50 / 1M	$0.00 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Nano Banana

2.0x cheaper monthly runtime

Speed

Nano Banana

+253% faster generation

Context

Nano Banana

32.8K tokens window

Punteggi Benchmark Verificati

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

Nano BananaGPT Image 1.5

SWE-bench Verified (Autonomous Coding)

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

N/Avs52%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs66%

MMLU-Pro (Multi-task Language Understanding)

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

N/Avs78.5%

LMSYS Chatbot Arena Elo

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

1360ptsvs1315pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs9.2%

Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs30.5%

SciCode (Scientific Computing)

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

N/Avs32%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs56.5%

AIME (Advanced Math Competition)

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

N/Avs84%

Long-Context Reasoning

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

N/Avs68.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

60 tok/s vs17 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

Nano Banana0.90s

GPT Image 1.57.10s

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

Nano Banana9.23s

GPT Image 1.536.51s

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)

Nano Banana Monthly API Bill

$21.75 / month

$2/1M in · $20/1M out

GPT Image 1.5 Monthly API Bill

$43.50 / month

$5/1M in · $40/1M out

Nano Banana saves approximately $21.75 / month (50%) under this workload.2.0x Savings

Nano Banana · Strengths & Key Advantages

Finestra di contesto da 33K con capacità massima di output fino a 8K token (Arena Elo 1360)
Throughput elevato di 60 token/secondo con latenza al primo token (TTFT) di soli 900 ms
Economia API competitiva ($2/$20 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 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

Token Use & Task Economics

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

Metric	Nano Banana	GPT Image 1.5
Cost per Task Estimated USD to finish one task	$0.03	$0.34
Output Tokens / Task Tokens generated per task	1K	9K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Nano Banana	GPT Image 1.5
Official API Model ID (SDK)	models/nano-banana	gpt-image-1-5
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	OpenAI Responses API & Chat Completions v1
Release Date	2025-08	2025-11
Knowledge Cutoff	June 2025	October 2025
Architecture	Conversational in-context image generation and editing transformer	Native multimodal image generation transformer
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 ($2/1M in) across full 33K window	Flat rate ($5/1M in) across full 4K window
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.5/1M with configurable TTL	Automatic prefix caching at $0/1M (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	Prompt-based JSON extraction only
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)	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	text, vision
Output Modalities	image	image

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

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

Nano Banana is more intelligent. It scores 75 compared with 46 on the composite Intelligence Index.

Which model is faster?

Nano Banana is faster, generating 60 tokens per second compared with 17 tokens per second.

Which model is cheaper to run?

Nano Banana is cheaper at $2.75 per 1M tokens blended, compared with $5.00 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nano Banana has lower latency, with a time to first token of 0.90s compared with 7.10s.

Which model has a larger context window?

Nano Banana has a larger context window, supporting 32.8K tokens compared with 4.1K tokens.

Verdetto

Sia Nano Banana (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 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.) eccellono in produzione: Nano Banana guida nei benchmark di ragionamento e programmazione, Nano Banana garantisce una generazione più rapida e Nano Banana offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

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

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

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

Nano Banana costa $2.00 / $20.00 per milione di token di input/output, mentre GPT Image 1.5 costa $5.00 / $40.00. Nel costo combinato, Nano Banana risulta più economico.

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

Nano Banana supporta 32.8K token di contesto contro 4.1K token di GPT Image 1.5, mentre Nano Banana 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)

Nano Banana vs GPT Image 1.5

Cambia e Confronta Qualsiasi Modello

Nano Banana

GPT Image 1.5

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Nano Banana · Strengths & Key Advantages

Considerations & Trade-offs

GPT Image 1.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

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

Verdetto

Domande Frequenti (FAQ)

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