GetInfoUs
Head-to-Head Model Comparison

GPT Image 2 vs GPT Image 1.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
Teilen
Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GPT Image 2 vs GPT Image 1.5: Benchmarks, Pricing & Speed Comparison

GPT Image 2 von OpenAI und GPT Image 1.5 von OpenAI gehören zu den führenden KI-Modellen. GPT Image 2 bietet ein Kontextfenster von 4.1K Tokens bei API-Preisen von $5.00/$40.00 pro 1M Tokens, während GPT Image 1.5 4.1K Tokens Kontext zu $5.00/$40.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

Beliebige Modelle wechseln & vergleichen

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
OpenAI

GPT Image 2

KI-Bildgenerierungsmodell

GPT Image 2 von OpenAI ist ein KI-Modell für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering mit 4K Kontextfenster, 21 Token/s Durchsatz, einem Intelligenz-Index von 59/100 und $5/$40 pro 1M Token.

Intelligence Index59 / 100
Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

68.5%

OpenAI

GPT Image 1.5

KI-Bildgenerierungsmodell

GPT Image 1.5 von OpenAI ist ein KI-Modell für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering mit 4K Kontextfenster, 17 Token/s Durchsatz, einem Intelligenz-Index von 46/100 und $5/$40 pro 1M Token.

Intelligence Index46 / 100
Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

52%

Wichtigste Unterschiede auf einen Blick

  • Both models cost the same under this workload — choose on capability, not price.
  • GPT Image 2 is faster at 21 tok/s vs 17 tok/s.
  • GPT Image 2 leads on SWE-bench coding (68.5% vs 52.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT Image 2GPT Image 1.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5946
Provider
OpenAIOpenAI
Input Price
Cost per million input tokens
$5.00 / 1M$5.00 / 1M
Output Price
Cost per million output tokens
$40.00 / 1M$40.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$5.00 / 1M$5.00 / 1M
Context Window
Maximum input + output tokens
4.1K tokens~6 A4 pages of text4.1K tokens~6 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
21 tok/s17 tok/s
SWE-bench Verified
Real-world software engineering
68.5%52%
GPQA Diamond
Graduate-level reasoning
72.5%66%

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
GPT Image 2
+16.5% SWE-bench lead
Cost
Tied
Identical monthly runtime cost
Speed
GPT Image 2
+24% faster generation
Context
Tied
4.1K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

GPT Image 2GPT Image 1.5
SWE-bench Verified (Autonomous Coding)

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

68.5%vs52%
GPQA Diamond (Doctorate-Level Science & Math)

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

72.5%vs66%
MMLU-Pro (Multi-task Language Understanding)

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

84.8%vs78.5%
LMSYS Chatbot Arena Elo

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

1375ptsvs1315pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

12.2%vs9.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

41.5%vs30.5%
SciCode (Scientific Computing)

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

40%vs32%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

67%vs56.5%
AIME (Advanced Math Competition)

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

89.6%vs84%
Long-Context Reasoning

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

78%vs68.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

21 tok/s vs17 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
GPT Image 26.20s
GPT Image 1.57.10s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT Image 230.01s
GPT Image 1.536.51s

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)
GPT Image 2 Monthly API Bill
$43.50 / month
$5/1M in · $40/1M out
GPT Image 1.5 Monthly API Bill
$43.50 / month
$5/1M in · $40/1M out
These models cost the same under this workload — no savings either way.Break-even

GPT Image 2 · Strengths & Key Advantages

  • 4K Kontextfenster und bis zu 4K maximale Output-Token (SWE-bench Verified 68.5% · GPQA Diamond 72.5%)
  • Hohe Generierungsgeschwindigkeit von 21 Token/Sekunde bei nur 6200 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

GPT Image 1.5 · Strengths & Key Advantages

  • 4K Kontextfenster und bis zu 4K maximale Output-Token (SWE-bench Verified 52% · GPQA Diamond 66%)
  • Hohe Generierungsgeschwindigkeit von 17 Token/Sekunde bei nur 7100 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.

MetricGPT Image 2GPT Image 1.5
Cost per Task
Estimated USD to finish one task
$0.36$0.34
Output Tokens / Task
Tokens generated per task
9K9K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureGPT Image 2GPT Image 1.5
Official API Model ID (SDK)gpt-image-2gpt-image-1-5
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2026-042025-11
Knowledge CutoffMarch 2026October 2025
ArchitectureFrontier native multimodal image 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 ($5/1M in) across full 4K windowFlat rate ($5/1M in) across full 4K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0/1M (no extra cache-write fee)Automatic prefix caching at $0/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingPrompt-based JSON extraction onlyPrompt-based JSON extraction only
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpenAI 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 Modalitiestext, visiontext, vision
Output Modalitiesimageimage

GPT Image 2 vs GPT Image 1.5: Schnelle Antworten (FAQ)

Which is more intelligent, GPT Image 2 or GPT Image 1.5?

GPT Image 2 is more intelligent. It scores 59 compared with 46 on the composite Intelligence Index.

Which model is faster?

GPT Image 2 is faster, generating 21 tokens per second compared with 17 tokens per second.

Which model has lower latency?

GPT Image 2 has lower latency, with a time to first token of 6.20s compared with 7.10s.

Fazit

Sowohl GPT Image 2 (Optimal für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch GPT Image 1.5 (Optimal für hochauflösende KI-Bildgenerierung, visuelles Design und präzises Text-Rendering, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: GPT Image 2 führt bei komplexem Reasoning und Coding, GPT Image 2 liefert den höheren Token-Durchsatz und GPT Image 2 ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – GPT Image 2 oder GPT Image 1.5?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt GPT Image 2 vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von GPT Image 2 und GPT Image 1.5?+

GPT Image 2 kostet $5.00 / $40.00 pro 1M Input-/Output-Tokens, GPT Image 1.5 liegt bei $5.00 / $40.00. Beim gewichteten Gesamtpreis ist GPT Image 2 günstiger.

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

GPT Image 2 bietet 4.1K Tokens Kontext gegenüber 4.1K Tokens bei GPT Image 1.5. Bei der Generierungsgeschwindigkeit liegt GPT Image 2 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 OpenAI und OpenAI, Systemkarten und unabhängige Benchmark-Auswertungen (2026).