DeepSeek: DeepSeek V4.1 Flash 1017
deepseek/deepseek-v4.1-flash-1017DeepSeek V4.1 Flash 1017 is an update for programming, analysis and multistep project work with text output.
DeepSeek V4.1 Flash 1017 is an update to DeepSeek V4.1 Flash released on October 17, 2026. The developer associates it with advances in reasoning, programming and agentic tasks. Its training uses reinforcement learning with self-generated feedback, intended to improve project work from the initial concept through successive refinements. This is a distinct model version that you can select by the listing’s exact name.
Working on a project
Use the model when you need to maintain several related requirements while working through a series of decisions: analyze a task, make a plan, prepare code and describe verification. The official announcement showcases games and three-dimensional scenes. For text work in Ailoot API, these areas translate into tasks involving code, scripts and technical instructions.
- Provide a project description and ask for it to be divided into working stages.
- Add the existing code, expected behavior and error description to obtain an analysis and a proposed change.
- Supply several approaches and selection criteria so the model can prepare a reasoned comparison.
- Ask it to connect a change to a test scenario and list the conditions under which the result needs to be checked.
Analysis and continued work
For a long task, keep the goal, accepted decisions and current section of work in the request. After an initial response, for example, you can clarify library or data-format constraints and then ask it to revise only the relevant section. When analyzing documents, specify the questions and the passages to use: the output might be a summary, a discrepancy list, a draft specification or an explanation of a complex topic.
Output format
This Ailoot API listing accepts text and returns text. It can produce explanations, plans, program code and scene descriptions. For a three-dimensional project, request a script or a sequence of editor actions; execution takes place in the appropriate working environment.
For the Messages and Responses methods, the listing specifies a context of up to 1,048,576 tokens. When preparing a large request, account for conversation history and supplied material. Separate the source data with clear headings and define the expected result in advance—for example, a brief conclusion, followed by source-based reasoning and a list of proposed changes.
Available through Ailoot API
POST /v1/messages- Input types
text- Output types
text- Context
- Not specified in the catalogue
- Max. output
- Not specified in the catalogue
- Input
- $0.0006 / 1K
- Output
- $0.0024 / 1K
- Cache read
- $0.000012 / 1K
POST /v1/responses- Input types
text- Output types
text- Context
- Not specified in the catalogue
- Max. output
- Not specified in the catalogue
- Input
- $0.0006 / 1K
- Output
- $0.0024 / 1K
- Cache read
- $0.000012 / 1K
POST /v1/chat/completions- Input types
text- Output types
text- Context
- Not specified in the catalogue
- Max. output
- Not specified in the catalogue
- Input
- $0.0006 / 1K
- Output
- $0.0024 / 1K
- Cache read
- $0.000012 / 1K
POST /v1beta/models/deepseek/deepseek-v4.1-flash-1017:generateContent- Input types
text- Output types
text- Context
- Not specified in the catalogue
- Max. output
- Not specified in the catalogue
- Input
- $0.0006 / 1K
- Output
- $0.0024 / 1K
- Cache read
- $0.000012 / 1K
deepseek/deepseek-v4.1-flash-1017 · JSON
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For text work in Ailoot API, these areas translate into tasks involving code, scripts and technical instructions.\n\n- Provide a project description and ask for it to be divided into working stages.\n- Add the existing code, expected behavior and error description to obtain an analysis and a proposed change.\n- Supply several approaches and selection criteria so the model can prepare a reasoned comparison.\n- Ask it to connect a change to a test scenario and list the conditions under which the result needs to be checked.\n\n### Analysis and continued work\n\nFor a long task, keep the goal, accepted decisions and current section of work in the request. After an initial response, for example, you can clarify library or data-format constraints and then ask it to revise only the relevant section. When analyzing documents, specify the questions and the passages to use: the output might be a summary, a discrepancy list, a draft specification or an explanation of a complex topic.\n\n### Output format\n\nThis Ailoot API listing accepts text and returns text. It can produce explanations, plans, program code and scene descriptions. For a three-dimensional project, request a script or a sequence of editor actions; execution takes place in the appropriate working environment.\n\nFor the Messages and Responses methods, the listing specifies a context of up to 1,048,576 tokens. When preparing a large request, account for conversation history and supplied material. 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