GPT Image 1 vs Imagen 4
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT Image 1 da OpenAI e Imagen 4 da Google são dois modelos de IA de destaque. O GPT Image 1 oferece uma janela de contexto de 4.1K tokens a $5.00/$40.00 por milhão de tokens, enquanto o Imagen 4 oferece 2K tokens de contexto a $40.00/$0.00 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.
GPT Image 1
Geração de Imagens por IAO GPT Image 1 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 14 tokens/s, índice de inteligência de 41/100 e tarifa de
$5.00 / 1M
$40.00 / 1M
4.1K tokens
38.8%
Imagen 4
Geração de Imagens por IAO Imagen 4 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 2K, velocidade de 25 tokens/s, índice de inteligência de 82/100 e tarifa de $40
$40.00 / 1M
$0.00 / 1M
2K tokens
N/A
Principais Diferenças em Resumo
- GPT Image 1 is 1.4x cheaper for API usage (input + output tokens combined).
- GPT Image 1 has a larger context window (4K vs 2K tokens).
- Imagen 4 is faster at 25 tok/s vs 14 tok/s.
| Feature | GPT Image 1 | Imagen 4 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 41 | 82 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $5.00 / 1M | $40.00 / 1M |
Output Price Cost per million output tokens | $40.00 / 1M | $0.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $5.00 / 1M | $8.00 / 1M |
Context Window Maximum input + output tokens | 4.1K tokens~6 A4 pages of text | 2K tokens~3 A4 pages of text |
Max Output Tokens Per single request | 4K | 4K |
Throughput Speed Tokens generated per second | 14 tok/s | 25 tok/s |
SWE-bench Verified Real-world software engineering | 38.8% | N/A |
GPQA Diamond Graduate-level reasoning | 53.6% | N/A |
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.
GPT Image 1 · Strengths & Key Advantages
- Janela de contexto de 4K com limite máximo de saída de 4K tokens (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
- Taxa de transferência rápida de 14 tokens/segundo com latência inicial (TTFT) de 8200 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
Imagen 4 · Strengths & Key Advantages
- Janela de contexto de 2K com limite máximo de saída de 4K tokens (Arena Elo 1390)
- Taxa de transferência rápida de 25 tokens/segundo com latência inicial (TTFT) de 2000 ms
- Economia de API competitiva ($40/$0 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 | GPT Image 1 | Imagen 4 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.32 | $0.04 |
Output Tokens / Task Tokens generated per task | 8K | 0K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT Image 1 | Imagen 4 |
|---|---|---|
| Official API Model ID (SDK) | gpt-image-1 | models/imagen-4 |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2025-04 | 2025-05 |
| Knowledge Cutoff | April 2025 | March 2025 |
| Architecture | Native multimodal image generation transformer | High-resolution multimodal image diffusion 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 ($5/1M in) across full 4K window | Flat rate ($40/1M in) across full 2K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) | Implicit + Explicit Context Caching at $0/1M with configurable TTL |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Text-only completion (No GUI action loop) |
| MCP & Parallel Tool Calling | Prompt-based JSON extraction only | Prompt-based JSON extraction only |
| 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) |
| 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 |
| Output Modalities | image | image |
GPT Image 1 vs Imagen 4: Respostas Rápidas (FAQ)
Which is more intelligent, GPT Image 1 or Imagen 4?
Imagen 4 is more intelligent. It scores 82 compared with 41 on the composite Intelligence Index.
Which model is faster?
Imagen 4 is faster, generating 25 tokens per second compared with 14 tokens per second.
Which model is cheaper to run?
GPT Image 1 is cheaper at $5.00 per 1M tokens blended, compared with $8.00 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Imagen 4 has lower latency, with a time to first token of 2.00s compared with 8.20s.
Which model has a larger context window?
GPT Image 1 has a larger context window, supporting 4.1K tokens compared with 2K tokens.
Veredito
Tanto GPT Image 1 (Indicado para geração de imagens em alta resolução, design visual e tipografia precisa, arquiteturas RAG corporativas e integração escalável via API.) quanto Imagen 4 (Indicado para geração de imagens em alta resolução, design visual e tipografia precisa, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Imagen 4 lidera em inteligência geral e programação, Imagen 4 oferece geração mais rápida e GPT Image 1 apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, GPT Image 1 ou Imagen 4?+
Nas avaliações de inteligência e código, Imagen 4 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, GPT Image 1 ou Imagen 4?+
O GPT Image 1 custa $5.00 / $40.00 por 1M de tokens (entrada/saída) e o Imagen 4 custa $40.00 / $0.00. No custo combinado, GPT Image 1 é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O GPT Image 1 suporta 4.1K tokens de contexto contra 2K tokens do Imagen 4, enquanto Imagen 4 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
- Imagen 3 vs. GPT Image 1: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Imagen 4 vs. Imagen 3: 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
- Aion-Mini vs. Laguna XS 2.1: 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 OpenAI e Google e benchmarks independentes (2026).