GPT Image 1 vs Imagen 4
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT Image 1 by OpenAI and Imagen 4 by Google 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 4 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 4 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.
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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%
Imagen 4
Image de pointede pointe image génération moteur offrant cinematic 4K résolution, complexe layouts, et ultra-fine typography.
$40.00 / 1M
$0.00 / 1M
2K tokens
N/A
Différences Clés en un Coup d’Œil
- 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.
| Caractéristique | 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 |
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.
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
Imagen 4 · Strengths & Key Advantages
- natif 4K rendering capacité
- Flawless rendering de multi-sentence dans-image texte
- profond compréhension d'artistic lenses et styles
Considerations & Trade-offs
- supérieur génération coût par image ($0.04)
- Longer rendering latence sur 4K mode
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 |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | 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: Réponses Rapides (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.
Verdict
Verdict & Model Selection Recommendation: Choose GPT Image 1 if your priority is Professional image generation, editing and branded visuals. Its performance in demanding tasks justifies its operational token cost. Choose Imagen 4 if your workflow prioritizes Professional advertising, print-ready media, and studio graphic design. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Questions fréquentes
How does GPT Image 1 compare to Imagen 4 in API token pricing and cost per token?+
GPT Image 1 costs $5.00 per 1M input tokens and $40.00 per 1M output tokens, whereas Imagen 4 costs $40.00 input and $0.00 output. Overall, GPT Image 1 is the more cost-effective model for high-volume API pipelines.
Which model has a larger context window: GPT Image 1 or Imagen 4?+
GPT Image 1 supports a context window of 4K tokens (~3k words), while Imagen 4 supports 2K tokens (~2k 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: GPT Image 1 or Imagen 4?+
GPT Image 1 scores 38.8% on SWE-bench Verified, while Imagen 4 scores competitively for software generation. 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 GPT Image 1 and Imagen 4?+
GPT Image 1 is optimized for low-latency direct generation. In contrast, Imagen 4 focuses on standard fast inference.
How does inference speed (tokens per second) compare between GPT Image 1 and Imagen 4?+
GPT Image 1 generates approximately 14 tokens per second, while Imagen 4 delivers 25 tokens per second. In latency-sensitive production environments, Imagen 4 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining GPT Image 1 and Imagen 4 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 4. 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