Nano Banana vs GPT Image 1.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Nano Banana da Google e GPT Image 1.5 da OpenAI são dois modelos de IA de destaque. O Nano Banana oferece uma janela de contexto de 32.8K tokens a $2.00/$20.00 por milhão de tokens, enquanto o GPT Image 1.5 oferece 4.1K tokens de contexto a $5.00/$40.00 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Nano Banana
Geração de Imagens por IAO Nano Banana da Google é um modelo de IA projetado para geração de imagens em alta resolução, design visual e tipografia precisa, oferecendo janela de contexto de 33K, velocidade de 60 tokens/s, índice de inteligência de 75/100 e tarifa de
$2.00 / 1M
$20.00 / 1M
32.8K tokens
N/A
GPT Image 1.5
Geração de Imagens por IAO GPT Image 1.5 da OpenAI é um modelo de IA projetado para geração de imagens em alta resolução, design visual e tipografia precisa, oferecendo janela de contexto de 4K, velocidade de 17 tokens/s, índice de inteligência de 46/100 e tarifa d
$5.00 / 1M
$40.00 / 1M
4.1K tokens
52%
Principais Diferenças em Resumo
- 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.
| Feature | Nano Banana | GPT Image 1.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 75 | 46 |
Provider | 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 |
Quem vence em cada categoria?
At-a-glance decision frameworkEvaluations ongoing
Pontuações de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Nano Banana · Strengths & Key Advantages
- Janela de contexto de 33K com limite máximo de saída de 8K tokens (Arena Elo 1360)
- Taxa de transferência rápida de 60 tokens/segundo com latência inicial (TTFT) de 900 ms
- Economia de API competitiva ($2/$20 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos
GPT Image 1.5 · Strengths & Key Advantages
- Janela de contexto de 4K com limite máximo de saída de 4K tokens (SWE-bench Verified 52% · GPQA Diamond 66%)
- Taxa de transferência rápida de 17 tokens/segundo com latência inicial (TTFT) de 7100 ms
- Economia de API competitiva ($5/$40 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos
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 |
Especificações Técnicas
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: Respostas Rápidas (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.
Veredito
Tanto Nano Banana (Indicado para geração de imagens em alta resolução, design visual e tipografia precisa, arquiteturas RAG corporativas e integração escalável via API.) quanto GPT Image 1.5 (Indicado para geração de imagens em alta resolução, design visual e tipografia precisa, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Nano Banana lidera em inteligência geral e programação, Nano Banana oferece geração mais rápida e Nano Banana apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, Nano Banana ou GPT Image 1.5?+
Nas avaliações de inteligência e código, Nano Banana leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, Nano Banana ou GPT Image 1.5?+
O Nano Banana custa $2.00 / $20.00 por 1M de tokens (entrada/saída) e o GPT Image 1.5 custa $5.00 / $40.00. No custo combinado, Nano Banana é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O Nano Banana suporta 32.8K tokens de contexto contra 4.1K tokens do GPT Image 1.5, enquanto Nano Banana entrega maior velocidade de geração.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- GPT Image 1.5 vs. Nano Banana Pro: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- GPT Image 2 vs. GPT Image 1.5: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Nano Banana Pro vs. Nano Banana: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Nano Banana vs. Imagen 4: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Aion-3.0 vs. Aion-Mini: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Aion-3.0 vs. Gemini 3.6 Flash: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Fontes oficiais: Documentação oficial de API da Google e OpenAI e benchmarks independentes (2026).