TabbitDeepSeek V4.1 Flash · Prompts and workflows
Browse executable prompts and workflows by task, content type, and runtime. Each card shows inputs, verification status, and the original source.
Runtimes vary by resource and may include an API, CLI, agent framework, or browser coding environment. Check each card for details.
Editor picks
Use deepseek-flash as the model name for the first call; the old aliases are still accepted, but requests are served by DeepSeek-V4.1-Flash and billed at Flash pricing. The official example uses an OpenAI-compatible format, thinking enabl
The current API uses deepseek-flash to access DeepSeek-V4.1-Flash; thinking mode is enabled by default with a default effort of high, request tiers map to low, high, or max according to the official mapping, and multi-turn requests with t
An English systemprompt that includes an example can make the DeepSeek API extract question-and-answer text into JSON; the call must also set responseformat to {'type': 'jsonobject'}. The official documentation also notes that the prompt
Tool calling is a two-stage, client-driven process: the model first returns toolcalls, the client executes the function and sends back the role="tool" result, and the model then generates the final answer. When strict beta is enabled, the
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Use deepseek-flash as the model name for the first call; the old aliases are still accepted, but requests are served by DeepSeek-V4.1-Flash and billed at Flash pricing. The official example uses an OpenAI-compatible format, thinking enabl
The current API uses deepseek-flash to access DeepSeek-V4.1-Flash; thinking mode is enabled by default with a default effort of high, request tiers map to low, high, or max according to the official mapping, and multi-turn requests with t
An English systemprompt that includes an example can make the DeepSeek API extract question-and-answer text into JSON; the call must also set responseformat to {'type': 'jsonobject'}. The official documentation also notes that the prompt
Tool calling is a two-stage, client-driven process: the model first returns toolcalls, the client executes the function and sends back the role="tool" result, and the model then generates the final answer. When strict beta is enabled, the
deepseek-flash (currently corresponding to DeepSeek-V4.1-Flash) accepts messages containing text and images through OpenAI-compatible Chat Completions; images can be supplied as Base64, a public URL, or a Files API fileid, and the choice
First have the model turn the requirements into one or more Markdown specification documents, then use those documents to drive implementation; the prompt asks the model to cover target customers, regions, parameters, technical scope, and
DeepSeek V4.1 Flash
After downloading, check the models and features available to your account. API and local-code steps still require their own runtime.