DeepSeek V4.1 Flash chat through an OpenAI-compatible endpoint. It takes up to 1,048,576 tokens of text and image context and returns up to 384,000, with low or high reasoning effort, up to 128 tool definitions and JSON format.
Workbench
These examples were written for this endpoint. Replace the prompt and sample media URLs with your own accessible inputs, then check the current quote and model availability before submitting.
- Input types
- Text
- Output types
- Text
- Input
- $0.30 / 1 million tokens
- Cached input
- $0.006 / 1 million tokens
- Output
- $1.20 / 1 million tokens
- Context
- 1,048,576
- Max output
- 384K
$0.30/1.20per 1 million tokens · input / output
triage Evidence, assumptions and next checks kept apart, at high effort - the default working setting.
- 700
- high
- Input types
- Text
- Output types
- Text
- Input
- $0.30 / 1 million tokens
- Cached input
- $0.006 / 1 million tokens
- Output
- $1.20 / 1 million tokens
- Context
- 1,048,576
- Max output
- 384K
$0.30/1.20per 1 million tokens · input / output
repo-review The escalation shape: same messages, effort at high and a 32,000-token cap for a long finding list.
- 32000
- high
- Input types
- Text
- Output types
- Text
- Input
- $0.30 / 1 million tokens
- Cached input
- $0.006 / 1 million tokens
- Output
- $1.20 / 1 million tokens
- Context
- 1,048,576
- Max output
- 384K
$0.30/1.20per 1 million tokens · input / output
json-extract response_format plus field names spelled out in the prompt, which is how you get the same keys back on every run.
- 4000
This example starts at Input $0.30 / Output $1.20 per 1 million tokens. The Playground updates the estimate when you change the settings.
