OpenAI
GPT-Image 2
OpenAI’s second-generation image model — instruction-precise synthesis, editing and in-image text.
Intelligenza
93.1 #8
AAQI 93.0
Velocità Uscita
25 t/s
ITL 40.0 ms/tok
Prezzo combinato (3:1)
$0.09 /1M
Input $0.09/M · Output $0.09/M
Contesto
128K
≈ 320 pagine A4 · output max 4,096
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
GPT-Image 2
Claude Mythos Preview (#1)
Average (68)
Gli assi radar sono approssimati dai punteggi di categoria dove mancano misurazioni dirette — vedi Metodologia.
Punti di forza e compromessi
Dove vince
- Best instruction-following in the image class
- Clean typography and UI-style text rendering
- First-class edit/inpaint endpoints
- Deep integration with OpenAI agents
A cosa fare attenzione
- Most expensive per-image tier
- Slower renders on complex scenes
- Closed weights
Casi d'uso killer
Design-to-asset pipelines
Prompt-precise banners, mockups and brand assets.
Agentic creative tools
Image calls orchestrated by GPT-6 agents.
Text-heavy graphics
Posters and slides needing real, legible copy.
Quickstart per sviluppatori e API
Imposta prima
OPENAI_API_KEY — ottieni una chiave APIcurl https://api.openai.com/v1/responses \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "gpt-image-2",
"input": "Refactor this function for O(n) time and explain the change."
}'from openai import OpenAI
client = OpenAI() # reads OPENAI_API_KEY
resp = client.responses.create(
model="gpt-image-2",
input="Refactor this function for O(n) time and explain the change.",
)
print(resp.output_text)const res = await fetch("https://api.openai.com/v1/responses", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
"content-type": "application/json",
},
body: JSON.stringify({ model: "gpt-image-2", input: "Refactor this function for O(n) time and explain the change." }),
});
console.log((await res.json()).output_text);Risorse e link ufficiali
Deployment API
Confronta host e latenza
Throughput, TTFT e prezzi cache su Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock e Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Punteggi per Fonte
Punteggi per Categoria
Risultati dei Benchmark
Scontri diretti live
Specifiche live e architettura
Sotto il cofano
GPT-Image 2 — OpenAI image generation
- Second-gen image stack trained with GPT-side prompt understanding
- Legible in-image text and dense layout control
- Transparent-background and masked-edit modes
- Tight GPT-6/Responses API integration
Data di Rilascio
16 ott 2026
Architettura
GPT-Image 2 — OpenAI image generation
Parametri
Not disclosed
Licenza
Proprietary
Finestra di Contesto
128,000 tokens
Output max
4,096 tokens
Modalità
text + image
Prezzi cache
lettura $0.02 · scrittura $0.11 /1M
Ragionamento
—
Prezzo Ingresso
$0.09/M
Prezzo Uscita
$0.09/M
Velocità Uscita
25 t/s
Tempo al Primo Token
—
Dati aggiornati
22 ott 2026
Stima bolletta mensile
Spesa mensile stimata
$0.00
Calcolo risparmio vs GPT-4o…
Cita e incorpora
Badge Markdown GitHub
Loading badge markdown...BibTeX
@misc{llmpodium2026gptimage2,
title = {Benchmark Analysis and Intelligence Evaluation of GPT-Image 2},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/gpt-image-2}
}Incorpora il badge del punteggio
Aggiungi un badge Podium Score live al tuo README su GitHub o Hugging Face — rimanda alla classifica live.
Anteprima
Markdown
Loading badge snippet...HTML
Loading badge snippet...Altri modelli di OpenAI
Modelli alternativi
Migliori alternative a GPT-Image 2 in base a capacità, prezzi e benchmark.