Imagen 3 vs GPT Image 1
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
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.
Changez et Comparez les Modèles
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Imagen 3
Génération d'imagesélevé-photorealism image génération modèle avec exceptionnel typography rendering et prompt alignment.
$30.00 / 1M
$0.00 / 1M
1K tokens
N/A
GPT Image 1
Génération d'images nativeun production image modèle pour génération, editing et brand-safe visuel flux de travail.
$5.00 / 1M
$40.00 / 1M
4.1K tokens
38.8%
Différences Clés en un Coup d’Œil
- 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.
| Caractéristique | 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% |
Qui gagne où ?
At-a-glance decision frameworkEvaluations ongoing
Scores de Benchmarks Vérifiés
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.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Imagen 3 · Strengths & Key Advantages
- supérieur typographic rendering inside images
- Stunning photorealistic skin tones et lighting
- faible artifact rate
Considerations & Trade-offs
- Strict sécurité filtering sur ambiguous concepts
- Contrôle limité de la composition multi-personnages
GPT Image 1 · Strengths & Key Advantages
- meilleur-dans-classe texte rendering inside images
- solide instruction-following pour edits et inpainting
- natif multimodal génération rather que un diffusion bolt-sur
- Handles complexe multi-element compositions reliably
Considerations & Trade-offs
- Expensive par image à échelle
- Slower que dédié diffusion modèles
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 |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | 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: Réponses Rapides (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.
Verdict
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.
Questions fréquentes
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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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs