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Head-to-Head Model Comparison

Imagen 3 vs GPT Image 1

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Imagen 3 vs GPT Image 1: Benchmarks, Pricing & Speed Comparison

Imagen 3 von Google und GPT Image 1 von OpenAI gehören zu den führenden KI-Modellen. Imagen 3 bietet ein Kontextfenster von 1K Tokens bei API-Preisen von $30.00/$0.00 pro 1M Tokens, während GPT Image 1 4.1K Tokens Kontext zu $5.00/$40.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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Popular Matchups:
Google

Imagen 3

KI-Bildgenerierungsmodell

Imagen 3 von Google ist ein KI-Modell für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering mit 1K Kontextfenster, 20 Token/s Durchsatz, einem Intelligenz-Index von 72/100 und $30/$0 pro 1M Token.

Intelligence Index72 / 100
Input Token:

$30.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

1K tokens

SWE-bench Verified:

N/A

OpenAI

GPT Image 1

KI-Bildgenerierungsmodell

GPT Image 1 von OpenAI ist ein KI-Modell für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering mit 4K Kontextfenster, 14 Token/s Durchsatz, einem Intelligenz-Index von 41/100 und $5/$40 pro 1M Token.

Intelligence Index41 / 100
Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

38.8%

Wichtigste Unterschiede auf einen Blick

  • 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.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureImagen 3GPT Image 1
Intelligence Index
Composite reasoning & knowledge score (0-100)
7241
Provider
GoogleOpenAI
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 text4.1K tokens~6 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
20 tok/s14 tok/s
SWE-bench Verified
Real-world software engineering
N/A38.8%
GPQA Diamond
Graduate-level reasoning
N/A53.6%

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
GPT Image 1
1.0x cheaper monthly runtime
Speed
Imagen 3
+43% faster generation
Context
GPT Image 1
4.1K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

Official evaluation metrics verified by independent third-party research labs.

Imagen 3GPT Image 1
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

N/Avs38.8%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

N/Avs53.6%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

N/Avs72.6%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1310ptsvs1286pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs4.1%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs18.5%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs27.3%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs43.9%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs29.7%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs58.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

20 tok/s vs14 tok/s

Latenz & Antwortzeit

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Imagen 32.50s
GPT Image 18.20s
Est. End-to-End Response (500 tokens)TTFT + generation time
Imagen 327.50s
GPT Image 143.91s

Interaktiver Token-Kosten-Simulator

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Imagen 3 Monthly API Bill
$45.00 / month
$30/1M in · $0/1M out
GPT Image 1 Monthly API Bill
$43.50 / month
$5/1M in · $40/1M out
GPT Image 1 saves approximately $1.50 / month (3%) under this workload.1.0x Savings

Imagen 3 · Strengths & Key Advantages

  • 1K Kontextfenster und bis zu 4K maximale Output-Token (Arena Elo 1310)
  • Hohe Generierungsgeschwindigkeit von 20 Token/Sekunde bei nur 2500 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($30/$0 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
  • Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
  • Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung

GPT Image 1 · Strengths & Key Advantages

  • 4K Kontextfenster und bis zu 4K maximale Output-Token (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
  • Hohe Generierungsgeschwindigkeit von 14 Token/Sekunde bei nur 8200 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($5/$40 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
  • Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
  • Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricImagen 3GPT Image 1
Cost per Task
Estimated USD to finish one task
$0.03$0.32
Output Tokens / Task
Tokens generated per task
0K8K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureImagen 3GPT Image 1
Official API Model ID (SDK)models/imagen-3gpt-image-1
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKOpenAI Responses API & Chat Completions v1
Release Date2024-082025-04
Knowledge CutoffJuly 2024April 2025
ArchitectureLatent text-to-image diffusion transformerNative multimodal image generation transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 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 windowFlat rate ($5/1M in) across full 4K window
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0/1M with configurable TTLAutomatic prefix caching at $0/1M (no extra cache-write fee)
Computer Use / GUI AgentText-only completion (No GUI action loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingPrompt-based JSON extraction onlyPrompt-based JSON extraction only
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision
Output Modalitiesimageimage

Imagen 3 vs GPT Image 1: Schnelle Antworten (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.

Fazit

Sowohl Imagen 3 (Optimal für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch GPT Image 1 (Optimal für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Imagen 3 führt bei komplexem Reasoning und Coding, Imagen 3 liefert den höheren Token-Durchsatz und GPT Image 1 ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Imagen 3 oder GPT Image 1?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Imagen 3 vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Imagen 3 und GPT Image 1?+

Imagen 3 kostet $30.00 / $0.00 pro 1M Input-/Output-Tokens, GPT Image 1 liegt bei $5.00 / $40.00. Beim gewichteten Gesamtpreis ist GPT Image 1 günstiger.

Welches Modell hat das größere Kontextfenster und die höhere Geschwindigkeit?+

Imagen 3 bietet 1K Tokens Kontext gegenüber 4.1K Tokens bei GPT Image 1. Bei der Generierungsgeschwindigkeit liegt Imagen 3 vorn.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

Offizielle Quellen: Offizielle API-Dokumentation von Google und OpenAI, Systemkarten und unabhängige Benchmark-Auswertungen (2026).