DeepSeek/deepseek-v4-flash-text-to-text-0731
deepseek-v4-flash-text-to-text-0731
Free to try DeepSeek v4 Flash Text API for fast, affordable text generation, summaries, writing, and automation workflows.
Text Chat
Related Deepseek V4 Flash 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: 'deepseek-v4-flash-text-to-text-0731',
messages: [
{
role: 'user',
content: 'Write a four-line modern poem about a programmer drinking coffee.'
}
],
stream: true,
max_tokens: 500,
top_p: 0.5,
top_k: 1
})
});
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': 'deepseek-v4-flash-text-to-text-0731',
'messages': [
{
'role': 'user',
'content': 'Write a four-line modern poem about a programmer drinking coffee.',
}
],
'stream': True,
'max_tokens': 500,
'top_p': 0.5,
'top_k': 1,
},
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": "deepseek-v4-flash-text-to-text-0731",
"messages": [
{
"role": "user",
"content": "Write a four-line modern poem about a programmer drinking coffee."
}
],
"stream": true,
"max_tokens": 500,
"top_p": 0.5,
"top_k": 1
}'
DeepSeek v4 Flash Text to Text 0731 Pricing
| Parameters | Price | Original Price | Discount |
|---|
README
Fast & Affordable DeepSeek v4 Flash Text-to-Text API (Rapid LLM Integration)
DeepSeek v4 Flash Text-to-Text API on Flaq AI provides fast, affordable LLM access for developers building chat, writing, summarization, coding support, and automation workflows. This DeepSeek Flash API integration turns user messages into responsive text outputs through a stable managed route with token-based billing. It is designed for high-volume products that need practical language generation, rapid iteration, and very affordable API usage without managing model infrastructure.
Key Features of DeepSeek v4 Flash Text-to-Text API
- Fast Text Generation: Generate useful responses quickly for chat products, internal tools, content workflows, and automation systems.
- Very Affordable API Access: Use DeepSeek v4 Flash for token-based text generation where speed, cost control, and high-volume throughput matter.
- Flexible LLM Output: Support writing, rewriting, summarization, classification, coding assistance, and structured response workflows.
- Prompt-Guided Control: Guide tone, format, response length, task scope, and output structure through system and user messages.
- Production-Friendly Integration: Add DeepSeek v4 Flash to applications through Flaq AI's stable chat completions route.
- Scalable Workflow Coverage: Build assistants, content tools, support bots, workflow agents, and batch text processing systems.
How to Use DeepSeek v4 Flash Text-to-Text API for Rapid LLM Generation on Flaq AI
- Input: Chat messages, system instructions, task context, and optional generation controls.
- Output: Fast text responses delivered through DeepSeek v4 Flash Text-to-Text API integration.
- Conversation Control: Supports prompt-based direction for tone, formatting, task boundaries, and multi-turn context.
- Capabilities: Rapid text-to-text generation, summarization, rewriting, coding help, structured output, and scalable LLM automation through DeepSeek v4 Flash API access.
Best Use Cases for DeepSeek v4 Flash Text-to-Text API Integration
- High-Volume Chat Products: Power assistants and user-facing chat features that need fast responses and affordable token usage.
- Content Drafting & Rewriting: Generate copy, summaries, titles, outlines, and text variants for production content workflows.
- Support & Operations Tools: Build internal copilots, ticket helpers, FAQ responders, and workflow automation features.
- Coding Assistance: Provide quick code explanations, draft snippets, and technical guidance for developer tools.
- Batch Text Processing: Run large-scale summarization, classification, extraction, and transformation jobs through a managed API route.
Note Please ensure prompts and generated content comply with DeepSeek and Flaq AI safety requirements. If an error occurs, revise the request, reduce unsupported content, or adjust generation settings and try again.
DeepSeek v4 Flash Text-to-Text vs Competitors: Comparative Analysis
- DeepSeek v4 Flash vs. DeepSeek v4 Pro Text-to-Text DeepSeek v4 Pro is positioned for stronger reasoning and more polished output. DeepSeek v4 Flash prioritizes faster, very affordable text generation for high-volume and iteration-heavy workflows.
- DeepSeek v4 Flash vs. DeepSeek v4 Flash Web Search DeepSeek v4 Flash Web Search adds web-connected retrieval for current-information workflows. DeepSeek v4 Flash Text-to-Text focuses on fast model-only responses for general language tasks.
- DeepSeek v4 Flash vs. GPT Mini Text Models GPT mini models offer fast general-purpose text generation. DeepSeek v4 Flash gives teams a DeepSeek-powered route for affordable LLM workflows through Flaq AI.
- DeepSeek v4 Flash vs. Qwen Flash Text Models Qwen Flash models provide Alibaba-powered fast text workflows. DeepSeek v4 Flash offers an alternative model behavior and pricing profile for scalable applications.
- DeepSeek v4 Flash vs. Kimi Text Models Kimi is useful for broad language reasoning and writing. DeepSeek v4 Flash focuses on rapid, cost-effective text-to-text generation for production integrations.