OpenAI GPT 5.4 API for multimodal LLM, visual Q&A, OCR, and image understanding. Stable and affordable for high-volume apps and production workflows. Built for free testing and stable API workflows.
Related Gpt 5.4 Models
API Examples
Submit Example
const response = await fetch('https://api.flaq.ai/api/v1/chat/completions', {
method: 'POST',
headers: {
Authorization: 'Bearer YOUR_API_KEY',
Accept: 'text/event-stream',
'Content-Type': 'application/json'
},
body: JSON.stringify({
model: 'gpt-5.4-image-to-text',
messages: [
{
role: 'user',
content: [
{ type: 'text', text: 'Describe the image and extract any visible text.' },
{
type: 'image_url',
image_url: {
url: 'https://example.com/sample-image.jpg'
}
}
]
}
],
stream: true,
max_tokens: 2048
})
});
const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
let assistantText = '';
while (true) {
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const frames = buffer.split('\n\n');
buffer = frames.pop() || '';
for (const frame of frames) {
const lines = frame.split('\n').filter(Boolean);
let eventName = 'message';
const dataLines = [];
for (const line of lines) {
if (line.startsWith('event:')) {
eventName = line.slice(6).trim();
} else if (line.startsWith('data:')) {
dataLines.push(line.replace(/^data:\s*/, ''));
}
}
const raw = dataLines.join('\n').trim();
if (raw === '[DONE]') {
console.log('\nFinal text:', assistantText);
continue;
}
let payload;
try {
payload = JSON.parse(raw);
} catch {
continue;
}
if (eventName === 'error' || payload.error) {
const msg = payload.error?.message ?? payload.message ?? 'Chat request failed';
throw new Error(msg);
}
const delta = payload.choices?.[0]?.delta;
if (delta?.content) {
assistantText += delta.content;
console.log(assistantText);
}
}
}
Submit Example
import json
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/chat/completions',
headers={
'Authorization': 'Bearer YOUR_API_KEY',
'Accept': 'text/event-stream',
'Content-Type': 'application/json',
},
json={
'model': 'gpt-5.4-image-to-text',
'messages': [
{
'role': 'user',
'content': [
{'type': 'text', 'text': 'Describe the image and extract any visible text.'},
{
'type': 'image_url',
'image_url': {
'url': 'https://example.com/sample-image.jpg'
}
},
],
}
],
'stream': True,
'max_tokens': 2048,
},
stream=True,
)
response.raise_for_status()
event_name = 'message'
assistant_text = ''
for raw_line in response.iter_lines(decode_unicode=True):
if not raw_line:
event_name = 'message'
continue
if raw_line.startswith('event:'):
event_name = raw_line.replace('event:', '', 1).strip()
continue
if raw_line.startswith('data:'):
raw_data = raw_line.replace('data:', '', 1).strip()
if raw_data == '[DONE]':
print('\nFinal text:', assistant_text)
continue
payload = json.loads(raw_data)
if event_name == 'error' or payload.get('error'):
error = payload.get('error') or payload
raise RuntimeError(error.get('message', 'Chat request failed'))
choices = payload.get('choices') or []
if choices:
delta = choices[0].get('delta') or {}
content = delta.get('content')
if content:
assistant_text += content
print(content, end='', flush=True)
Submit Example
curl -N -X POST "https://api.flaq.ai/api/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Accept: text/event-stream" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.4-image-to-text",
"messages": [
{
"role": "user",
"content": [
{ "type": "text", "text": "Describe the image and extract any visible text." },
{
"type": "image_url",
"image_url": {
"url": "https://example.com/sample-image.jpg"
}
}
]
}
],
"stream": true,
"max_tokens": 2048
}'
GPT 5.4 Image to Text Pricing
| Parameters | Price | Original Price | Discount |
|---|
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Fast & Affordable GPT 5.4 Image-to-Text API (a fast and affordable OpenAI model for professional AI workflows)
GPT 5.4 Image-to-Text API on Flaq AI provides OpenAI API access for professional workflows that need dependable reasoning, coding help, and practical chat experiences. This fast, affordable, and practical OpenAI API integration helps developers build image-to-text experiences with flexible conversation context, visual-analysis prompting, supported tool workflows, and route-specific settings on Flaq AI. Built for production workloads, it gives teams a stable way to add advanced AI capability without managing model infrastructure or writing provider-specific plumbing from scratch.
Key Features of GPT 5.4 Image-to-Text API
- High-Quality Vision Understanding: Analyze visual content, layout, objects, text, charts, and scene details through multimodal model reasoning.
- Precise Visual Instruction Following: Ask targeted questions about an image and receive focused answers for review, classification, extraction, or documentation.
- Flexible API Controls: Use conversation context, visual-analysis prompting, supported tool workflows, and route-specific settings on Flaq AI to guide simple requests, deep analysis, and production automation.
- Production Tool Support: Connect supported tool workflows, retrieval, automation, and advanced application features without surfacing low-level provider settings.
- Cost-Effective Integration: Build image-to-text features through Flaq AI with clear routing, stable model pages, and durable API messaging for production workflows.
- Developer-Friendly Workflow: Use natural-language instructions, structured prompts, and route-specific inputs to move quickly from prototype to production.
How to Use GPT 5.4 Image-to-Text API for Visual Analysis on Flaq AI
- Input: Uploaded image content plus natural-language instructions describing the analysis, extraction, or reasoning task.
- Output: Text descriptions, extracted details, visual reasoning, or structured summaries from uploaded images.
- Route Configuration: Designed for focused image understanding workflows with route-specific image input support.
- Configuration: flexible conversation context, visual-analysis prompting, supported tool workflows, and route-specific settings on Flaq AI.
- Capabilities: Image understanding, OCR-style extraction, visual QA, chart reading, product inspection, and multimodal reasoning through fast, affordable, and practical OpenAI API integration.
Best Use Cases for GPT 5.4 Image-to-Text API Integration
- Document & Screenshot Review: Extract key details from screenshots, forms, receipts, diagrams, and interface captures without manual transcription.
- Product & Catalog Analysis: Generate product descriptions, identify attributes, and summarize visual differences for ecommerce workflows.
- Chart & Diagram Interpretation: Turn visual data, charts, and architecture diagrams into clear text explanations for reports and planning.
- Creative Asset QA: Review ad creatives, social visuals, mockups, and design exports for consistency, issues, and content details.
- Accessibility Workflows: Produce image descriptions and visual summaries that make media easier to understand and reuse.
Note Please ensure your prompts, uploaded files, and application workflows comply with OpenAI safety and usage guidelines. If an error occurs, review the input for restricted content, simplify the request, and try again.
GPT 5.4 Image-to-Text vs Competitors: Comparative Analysis
-
GPT 5.4 vs. Claude Opus 4.7 Claude Opus 4.7 is strong for careful long-horizon reasoning and Claude-style agent workflows. GPT 5.4 offers OpenAI-native behavior, broad application tooling, and a familiar API path for teams already building on the OpenAI ecosystem.
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GPT 5.4 vs. Claude Sonnet 4.6 Claude Sonnet 4.6 focuses on a fast balance of intelligence and latency. GPT 5.4 is a strong choice when developers want OpenAI model behavior, flexible chat workflows, and integrated image-to-text capabilities on Flaq AI.
-
GPT 5.4 vs. Gemini Gemini models are attractive for Google-native multimodal and workspace-adjacent use cases. GPT 5.4 differentiates with OpenAI-style reasoning, dependable text quality, and production-friendly integration.
-
GPT 5.4 vs. DeepSeek Reasoner DeepSeek Reasoner is valued for affordable reasoning experiments. GPT 5.4 provides a managed API experience for professional image-to-text workflows, especially where reliability and ecosystem support matter.
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GPT 5.4 vs. Llama Llama models give teams open-model flexibility and deployment control. GPT 5.4 removes infrastructure overhead and delivers a scalable API for developers who need fast integration and consistent output quality.