deepseek/deepseek-v4-flash-0731
Release date: 2026-07-31
1,048,576 context · $0.14/M input tokens · $0.28/M output tokens
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows....
Pricing
Pay-per-use
No upfront costs, pay only for what you use
Try the model
API Usage
Use the following code examples to integrate with our API:
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'deepseek/deepseek-v4-flash-0731',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'deepseek/deepseek-v4-flash-0731',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Model Introduction
DeepSeek: DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows....
This model is imported from OpenRouter metadata and exposed through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.
Why It Looks Great
- text->text architecture for Text to Text workloads
- 1048576 context window for long prompts, document analysis, and multi-turn workflows
- Competitive pricing at $0.14/$0.28 per million tokens
- Function calling and tool-use support for agentic application workflows
- Structured output support for JSON responses and schema-constrained generation
- Reasoning controls available through supported OpenRouter parameters
Key Features
- Context Window: 1048576 tokens
- Max Input: 655360 tokens
- Max Output: 393216 tokens
- Vision: Not listed
- Function Calling: Supported
- Structured Outputs: Supported
- Image Generation: Not listed
- Audio Input: Not listed
- Supported Parameters: frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_a, top_k, top_logprobs, top_p
Specifications
| Specification | Value |
|---|---|
| Provider | deepseek |
| Model Type | Chat Completions model |
| Architecture | text->text |
| Context Window | 1048576 tokens |
| Max Input | 655360 tokens |
| Max Output | 393216 tokens |
| Input | Text |
| Output | Text |
| Vision | Not listed |
| Function Calling | Supported |
| Structured Outputs | Supported |
| OpenRouter Created | July 31, 2026 |
Pricing
| Token Type | Cost |
|---|---|
| Input | $0.14 per million tokens |
| Output | $0.28 per million tokens |
| Cached Input | $0.028 per million tokens |
Note: Pricing is generated from OpenRouter model metadata. If multiple upstream providers expose different endpoint prices, review and adjust the price before publishing.
How to Use
- Write your prompt - describe the task, provide context, and specify the desired output format.
- Submit - the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: deepseek/deepseek-v4-flash-0731
API Usage
Python SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="deepseek/deepseek-v4-flash-0731",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "deepseek/deepseek-v4-flash-0731",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: deepseek/deepseek-v4-flash-0731
- Provider: deepseek
- Endpoint availability and provider-specific routing may change on OpenRouter
Sources: OpenRouter model metadata.
Info
Supported Functionality
API Access Guide
DeepSeek V4 Flash 0731 API
deepseek/deepseek-v4-flash-0731
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows....
Input
$0.14 /M
Output
$0.28 /M
Context
1049K
Max Output
393K
Tool Use
Supported
Try DeepSeek V4 Flash 0731 on WaveSpeedAI
Access DeepSeek V4 Flash 0731 through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about DeepSeek V4 Flash 0731
How much does DeepSeek V4 Flash 0731 cost via the API?+
Pricing on WaveSpeedAI: $0.14 per million input tokens and $0.28 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of DeepSeek V4 Flash 0731?+
DeepSeek V4 Flash 0731 supports up to 1049K tokens of context with up to 393K tokens of output per request.
Is DeepSeek V4 Flash 0731 OpenAI-compatible?+
WaveSpeedAI exposes DeepSeek V4 Flash 0731 at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.
How do I get started with DeepSeek V4 Flash 0731?+
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.