Post-trained 0731 release with major gains across coding, repository work, tool use, and full-stack tasks, plus a 1M context window.
DeepSeekText Generation1M contextReleased Jul 31, 2026GermanyProprietary EndpointNewPost-trained 0731 release with major gains across coding, repository work, tool use, and full-stack tasks, plus a 1M context window.
Supports text input, hybrid thinking with enable_thinking and thinking_budget, function calling, strict JSON Schema output, and optional Linkup web search. Thinking tokens are billed as output tokens.
Also known as DeepSeek Flash 0731
deepseek-v4-flash-0731/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1beta/models/deepseek-v4-flash-0731:generateContentdeepseek/deepseek-v4-flash-0731deepseek-ai/deepseek-v4-flash-0731Live pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
DeepSeek V4 Flash 0731 serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id deepseek-v4-flash-0731. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-flash-0731",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'from openai import OpenAI
client = OpenAI(
base_url="https://api.empiriolabs.ai/v1",
api_key="YOUR_EMPIRIOLABS_API_KEY",
)
response = client.chat.completions.create(
model="deepseek-v4-flash-0731",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Request parameters supported by the DeepSeek V4 Flash 0731 API on EmpirioLabs. Defaults apply when a field is omitted.
| Parameter | Type | Default | Range / values | Description |
|---|---|---|---|---|
| temperature | number | 0.7 | 0 to 2 | Sampling temperature. 0 = deterministic, 2 = maximum randomness. |
| top_p | number | 0.9 | 0 to 1 | Nucleus sampling probability mass. Lower = more focused. |
| max_tokens | number | 4096 | 1 to 393216 | Maximum output tokens. |
| stop | string | - | - | Up to 4 strings where the model will stop generating further tokens. |
| enable_thinking | boolean | true | - | Enable step-by-step reasoning before answering. |
| reasoning_effort | enum | medium | none, low, medium, high, max | Reasoning effort level. none disables thinking. low, medium, high, and max set bounded thinking budgets sized to the selected model. Sent as an OpenAI-style... |
| thinking_budget | number | 32768 | 1 to 393216 | Maximum tokens reserved for the reasoning process. Up to 393216. |
| response_format | enum | - | - | Constrain the output to JSON. Use JSON mode for any valid JSON object, or JSON schema to force output that matches a schema you provide. |
| web_search_linkup | boolean | false | - | Optional web search powered by Linkup. When enabled, recent web sources are retrieved using your latest user message as the query and provided to the model as additional context. Adds $0.013 per call when invoked on top of the model's normal token cost. Disabled by default. |
| disable_formatting | boolean | false | - | When enabled, the gateway will not append the "Sources" footer to assistant responses that used Linkup web search. Useful when the model output is piped to another... |
Thinking is enabled by default and can be disabled. Reasoning tokens are billed as output tokens. Optional Linkup web search is billed only when invoked.
On EmpirioLabs, DeepSeek V4 Flash 0731 is billed pay as you go: Input $0.14 per 1M prompt tokens; Output $0.28 per 1M generated tokens; Web Search (Linkup) $0.013 per call when invoked. The live rate card on this page always matches what the API charges.
DeepSeek V4 Flash 0731 supports a 1M-token context window with up to 393,216 output tokens per response.
Yes. DeepSeek V4 Flash 0731 serves the OpenAI-compatible Chat Completions API, so existing OpenAI SDKs work by pointing base_url at https://api.empiriolabs.ai/v1 and setting the model id to deepseek-v4-flash-0731.
Yes. The EmpirioLabs playground runs DeepSeek V4 Flash 0731 in the browser with the same parameters the API exposes, so you can test prompts before writing code.
Create an EmpirioLabs account, then generate a key under API Keys in the dashboard. Billing is pay-as-you-go credits, so you only pay for the requests you make.
Check out our pricing or reach out if you want your own model deployed on our stack.
