Choose DeepSeek V4.1 Flash, V4 Pro or V4 Flash to work with a written question, code excerpt or document passage. Provide the source facts, explain the requested operation and define the answer format. All three current entries offer Chat Completions; V4.1 Flash also offers Responses. Select the model’s available output controls, read the complete reply and actual usage, then continue with relevant context or test feedback.
DeepSeek is developed by DeepSeek. Vidgo provides access to the models. Model names and trademarks belong to their respective owners.Open the model card to inspect its current conversation format, output settings and token prices. Use V4.1 Flash when you want to choose between Chat Completions and Responses, or review either V4 entry for the existing Chat Completions workflow.
DeepSeek V4.1 Flash combines image understanding, coding, and long-document analysis with a 1M-token context window.
DeepSeek V4 Pro handles long-context reasoning, coding, and document analysis with a 1M-token context window.
DeepSeek V4 Flash handles long-context chat, coding assistance, and document analysis with a 1M-token context window.
Use messages for Chat Completions, keeping the relevant user and assistant turns with the source text. V4.1 Flash also accepts a Responses workflow using input, with instructions for persistent guidance. Choose the supported output-token and sampling settings of the selected task. For V4 Pro, the online top_p setting uses a value greater than zero and at most one.
| Model / task | Input and workflow |
|---|---|
| DeepSeek V4.1 Flash | DeepSeek V4.1 Flash combines image understanding, coding, and long-document analysis with a 1M-token context window. |
| DeepSeek V4 Pro | DeepSeek V4 Pro handles long-context reasoning, coding, and document analysis with a 1M-token context window. |
| DeepSeek V4 Flash | DeepSeek V4 Flash handles long-context chat, coding assistance, and document analysis with a 1M-token context window. |
DeepSeek V4.1 Flash brings together coding, reasoning and task-planning capabilities. The following charts show its published capability comparisons and broader benchmark results. Compare the named tasks and model versions, then choose the available DeepSeek model that matches the problem you want to solve.
The capability chart compares terminal tasks, software engineering, security analysis and business-process automation. It shows how V4.1 Flash performs across these evaluation environments. For a development task, supply the code and operating context, describe the required change, and ask for an implementation or debugging plan with clear verification steps.
The benchmark table covers knowledge, mathematical reasoning, programming and agent tasks, with the evaluated model versions shown in its columns. Use these results to identify relevant strengths for your workload. Provide the original facts, required output structure and completion criteria when requesting a technical explanation, structured analysis or solution.
Prepare the document, code or business facts that the answer needs to use. Specify the operation, required structure and acceptance criteria, then review the returned text against the source. Continue with observed test results or clarified requirements when the task needs another iteration.
Provide the relevant functions and describe the behavior you want to trace. Ask for an explanation tied to the supplied code, then compare it with execution or test evidence before making a change.
Supply the sections that contain the relevant evidence and state the question. Request an answer organized around the needed facts and verify its statements against the original passages.
Provide a source description and the fields and units needed by your workflow. Validate the generated structure and values before using them in a catalog draft or application input.
Describe the reader’s issue, permitted actions and information still needed. Review the generated reply for factual accuracy, tone and an actionable next step before using it in a business workflow.
Provide the initial code or draft and add the observed result of your checks. Request the next revision, then use the same acceptance criteria to review the updated answer.
Use Chat Completions for the current V4 Pro or V4 Flash entry, or choose between that format and Responses for V4.1 Flash. Review the required fields, output settings and full token cost for your chosen workflow.
The table reads each DeepSeek model’s current starting input-token rate per one million tokens. A full request also includes the selected model’s output-token charge, and V4.1 Flash additionally lists a cache-read rate. Relevant conversation history contributes to input usage. Review the task’s complete rate table and returned usage when comparing a single answer or several coding and document-analysis iterations.
| Model | Provider | Workflow | Input | API formats | Starting input rate |
|---|---|---|---|---|---|
| DeepSeek V4.1 Flash | DeepSeek | Chat | Text instructions and conversation context | Chat Completions / Responses | $0.3 / 1M tokens |
| DeepSeek V4 Pro | DeepSeek | Chat | Text instructions and conversation context | Chat Completions | $0.342 / 1M tokens |
| DeepSeek V4 Flash | DeepSeek | Chat | Text instructions and conversation context | Chat Completions | $0.112 / 1M tokens |
Test a complete text task online, then integrate the selected model and API format.
Open the selected model, provide the task and source text, and choose its available output settings. Submit the conversation, read the complete answer and inspect available token usage. Add clarifications or test feedback when preparing a follow-up.
Use the existing model conversation, current token prices and task documentation to connect a reviewed answer with your application workflow.
Choose V4.1 Flash for Chat Completions or Responses, or select V4 Pro or V4 Flash for their current Chat Completions entries. Review the selected model’s full token-price table and output settings, then test the task with the source material you intend to use.
Open the selected model, provide the task and source text, and choose its available output settings. Submit the conversation, read the complete answer and inspect available token usage. Add clarifications or test feedback when preparing a follow-up.
The table reads each DeepSeek model’s current starting input-token rate per one million tokens. A full request also includes the selected model’s output-token charge, and V4.1 Flash additionally lists a cache-read rate. Relevant conversation history contributes to input usage. Review the task’s complete rate table and returned usage when comparing a single answer or several coding and document-analysis iterations.
Send model and messages to /v1/chat/completions for any of the three entries. V4.1 Flash also offers /v1/responses with model and input, plus optional instructions. Authenticate with your Vidgo API credentials, consume the selected response format and inspect the returned text and usage fields.
Use your Vidgo API credentials to authenticate the request to the selected endpoint. Send the exact model identifier, the conversation fields required by that protocol and the supported output settings. Consume the returned response using the same format you selected.
Accumulate streaming text when the selected workflow streams, or read the complete response body when it returns a full reply. Inspect the final answer and returned usage fields, then keep the relevant messages for the next turn. Return to the model conversation when continuing the online task.
Choose DeepSeek V4.1 Flash, V4 Pro or V4 Flash to work with a written question, code excerpt or document passage. Provide the source facts, explain the requested operation and define the answer format. All three current entries offer Chat Completions; V4.1 Flash also offers Responses. Select the model’s available output controls, read the complete reply and actual usage, then continue with relevant context or test feedback.
Read language-model introductions, API guides and platform comparisons to understand model selection, conversation inputs, response formats and token costs.
