Imagen 3 vs GPT Image 1
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Imagen 3 by Google and GPT Image 1 by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, GPT Image 1 holds a notable pricing advantage for token ingestion. On output generation, Imagen 3 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, GPT Image 1 provides an expanded memory horizon with 4K tokens. In latency-sensitive production environments, Imagen 3 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
원하는 AI 모델 선택 및 실시간 비교
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Imagen 3
플래그십 프론티어 모델Google의 Imagen 3 모델은 1K 토큰 컨텍스트 윈도우와 입력 $30/1M 토큰, 출력 $0/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$30.00 / 1M
$0.00 / 1M
1K tokens
N/A
GPT Image 1
플래그십 프론티어 모델OpenAI의 GPT Image 1 모델은 4K 토큰 컨텍스트 윈도우와 입력 $5/1M 토큰, 출력 $40/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$5.00 / 1M
$40.00 / 1M
4.1K tokens
38.8%
한눈에 보는 핵심 차이점
- GPT Image 1 is 1.0x cheaper for API usage (input + output tokens combined).
- GPT Image 1 has a larger context window (4K vs 1K tokens).
- Imagen 3 is faster at 20 tok/s vs 14 tok/s.
| Feature | Imagen 3 | GPT Image 1 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 72 | 41 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $30.00 / 1M | $5.00 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $40.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $6.00 / 1M | $5.00 / 1M |
Context Window Maximum input + output tokens | 1K tokens~2 A4 pages of text | 4.1K tokens~6 A4 pages of text |
Max Output Tokens Per single request | 4K | 4K |
Throughput Speed Tokens generated per second | 20 tok/s | 14 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 38.8% |
GPQA Diamond Graduate-level reasoning | N/A | 53.6% |
부문별 우위 모델
At-a-glance decision frameworkEvaluations ongoing
검증된 벤치마크 점수 비교
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.
지연 시간(Latency) 및 응답 속도
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
실시간 API 토큰 비용 시뮬레이터
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Imagen 3 · Strengths & Key Advantages
- Google의 첨단 Latent text-to-image diffusion transformer 아키텍처와 최대 1K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $30/1M, 출력 $0/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
GPT Image 1 · Strengths & Key Advantages
- OpenAI의 첨단 Native multimodal image generation transformer 아키텍처와 최대 4K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $5/1M, 출력 $40/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Imagen 3 | GPT Image 1 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.03 | $0.32 |
Output Tokens / Task Tokens generated per task | 0K | 8K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | Imagen 3 | GPT Image 1 |
|---|---|---|
| Official API Model ID (SDK) | models/imagen-3 | gpt-image-1 |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-08 | 2025-04 |
| Knowledge Cutoff | July 2024 | April 2025 |
| Architecture | Latent text-to-image diffusion 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 ($30/1M in) across full 1K window | Flat rate ($5/1M in) across full 4K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0/1M with configurable TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Text-only completion (No GUI action loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Prompt-based JSON extraction only | 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) | 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 | text, vision |
| Output Modalities | image | image |
Imagen 3 vs GPT Image 1: 핵심 요약 문답 (FAQ)
Which is more intelligent, Imagen 3 or GPT Image 1?
Imagen 3 is more intelligent. It scores 72 compared with 41 on the composite Intelligence Index.
Which model is faster?
Imagen 3 is faster, generating 20 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 $6.00 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Imagen 3 has lower latency, with a time to first token of 2.50s 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 1K tokens.
종합 평가
Verdict & Model Selection Recommendation: Choose Imagen 3 if your priority is Commercial asset generation, marketing collateral, and creative art direction. Its performance in demanding tasks justifies its operational token cost. Choose GPT Image 1 if your workflow prioritizes Professional image generation, editing and branded visuals. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
자주 묻는 질문 (FAQ)
How does Imagen 3 compare to GPT Image 1 in API token pricing and cost per token?+
Imagen 3 costs $30.00 per 1M input tokens and $0.00 per 1M output tokens, whereas GPT Image 1 costs $5.00 input and $40.00 output. Overall, GPT Image 1 is the more cost-effective model for high-volume API pipelines.
Which model has a larger context window: Imagen 3 or GPT Image 1?+
Imagen 3 supports a context window of 1K tokens (~1k words), while GPT Image 1 supports 4K tokens (~3k words). Therefore, GPT Image 1 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Imagen 3 or GPT Image 1?+
Imagen 3 scores at the frontier of coding benchmarks, while GPT Image 1 scores 38.8%. For complex autonomous debugging and agentic engineering, GPT Image 1 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between Imagen 3 and GPT Image 1?+
Imagen 3 is optimized for low-latency direct generation. In contrast, GPT Image 1 focuses on standard fast inference.
How does inference speed (tokens per second) compare between Imagen 3 and GPT Image 1?+
Imagen 3 generates approximately 20 tokens per second, while GPT Image 1 delivers 14 tokens per second. In latency-sensitive production environments, Imagen 3 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Imagen 3 and GPT Image 1 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT Image 1 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Imagen 3. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
공식 출처: GetInfoUs Independent AI Benchmarks & Official API Specs