Use Kimi 2.7 Image-to-Text API for visual understanding, image Q&A, OCR-style extraction, and multimodal reasoning in stable production workflows.
Related Kimi 2.7 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: 'kimi-2.7-image-to-text',
messages: [
{
role: 'user',
content: [
{
type: 'text',
text: 'What is roughly shown in this image?'
},
{
type: 'image_url',
image_url: {
url: 'https://example.com/sample-image.jpg'
}
}
]
}
],
stream: true,
max_tokens: 300
})
});
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': 'kimi-2.7-image-to-text',
'messages': [
{
'role': 'user',
'content': [
{
'type': 'text',
'text': 'What is roughly shown in this image?',
},
{
'type': 'image_url',
'image_url': {
'url': 'https://example.com/sample-image.jpg',
},
},
],
}
],
'stream': True,
'max_tokens': 300,
},
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": "kimi-2.7-image-to-text",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is roughly shown in this image?"
},
{
"type": "image_url",
"image_url": {
"url": "https://example.com/sample-image.jpg"
}
}
]
}
],
"stream": true,
"max_tokens": 300
}'
Kimi 2.7 Image to Text Pricing
| Parameters | Price | Original Price | Discount |
|---|
README
Stable & Affordable Kimi 2.7 Image-to-Text API (Moonshot AI Vision Understanding)
Kimi 2.7 Image-to-Text API on Flaq AI provides Moonshot AI multimodal model access for visual understanding, image Q&A, OCR-style extraction, and image-grounded reasoning workflows. This affordable Kimi vision API integration helps developers transform image input into useful text descriptions, answers, summaries, and structured insights. It is built for teams that need stable image analysis without maintaining separate vision infrastructure.
Key Features of Kimi 2.7 Image-to-Text API
- Visual Understanding: Analyze image input and return clear text descriptions, explanations, and answers through Kimi 2.7 API integration.
- Image-Grounded Reasoning: Combine visual details with user questions to support product analysis, document review, creative feedback, and multimodal workflows.
- OCR-Style Extraction: Extract visible text, labels, interface content, and image details for downstream automation and data processing.
- Developer-Friendly API Access: Add image-to-text capabilities to applications through a stable Flaq AI route designed for production workflows.
- Flexible Prompt Guidance: Use natural-language instructions to ask for short captions, detailed analysis, structured summaries, or task-specific outputs.
- Affordable Vision Workflows: Build scalable visual analysis features with cost-effective Moonshot AI model access.
How to Use Kimi 2.7 Image-to-Text API for Visual Analysis on Flaq AI
- Input: Image input plus natural-language questions or analysis instructions.
- Output: Text responses describing visual content, extracting information, answering questions, or summarizing image details.
- Image Support: Works with common image-input workflows for product visuals, screenshots, documents, and creative assets.
- Capabilities: Image description, visual QA, OCR-style reading, multimodal reasoning, screenshot analysis, and structured visual summaries through Kimi 2.7 API integration.
Best Use Cases for Kimi 2.7 Image-to-Text API Integration
- Screenshot & UI Analysis: Convert app screenshots into explanations, bug notes, accessibility observations, and structured review output.
- Document & Form Review: Extract visible fields, labels, tables, and document details from images for internal tools and automation.
- E-commerce Image Understanding: Describe products, identify attributes, summarize catalog visuals, and support moderation or merchandising workflows.
- Creative Asset Feedback: Analyze compositions, visual styles, brand consistency, and campaign creatives with prompt-guided output.
- Multimodal AI Assistants: Let users upload images and ask natural-language questions inside support, education, and productivity products.
Note Please ensure image input and prompts comply with Moonshot AI and Flaq AI safety requirements. If an error occurs, adjust the image input or prompt and try again.
Kimi 2.7 Image-to-Text vs Competitors: Comparative Analysis
- Kimi 2.7 Image-to-Text vs. GPT Image-to-Text
GPT image understanding offers broad multimodal coverage. Kimi 2.7 Image-to-Text API provides a Moonshot AI alternative for teams that want affordable visual analysis through Flaq AI. - Kimi 2.7 Image-to-Text vs. Gemini Image-to-Text
Gemini is strong for Google-native visual reasoning. Kimi 2.7 gives developers another stable route for image descriptions, OCR-style extraction, and image Q&A. - Kimi 2.7 Image-to-Text vs. Claude Vision
Claude Vision is useful for careful image and document interpretation. Kimi 2.7 focuses on practical image-to-text workflows for scalable product integrations. - Kimi 2.7 Image-to-Text vs. Grok Image-to-Text
Grok Image-to-Text provides xAI model behavior for visual analysis. Kimi 2.7 offers Moonshot AI multimodal access for teams comparing provider behavior and response style. - Kimi 2.7 Image-to-Text vs. Qwen Vision Models
Qwen vision models are strong Alibaba options. Kimi 2.7 Image-to-Text API gives developers a Moonshot-powered alternative for production visual understanding.
