# DeepSeek V4.1 Flash 1017 API DeepSeek's DeepSeek V4.1 Flash 1017, through an OpenAI-compatible API. 7 providers quote it now, and each request goes to the offer with the lowest estimated charge that meets your rules. - Providers compete for each request. The exchange ranks the offers that meet your rules by estimated charge. It fixes your maximum charge before the first token, and you pay for the tokens that the model uses. - The OpenAI and Anthropic APIs. Use the OpenAI or Anthropic SDK that you have. Set the base URL and your key, and send deepseek-v4.1-flash-1017 as the model. - Your data rules. Send x-liquid-retention: none and only offers whose provider does not keep your content compete for the request. ## Facts - Model name: deepseek-v4.1-flash-1017 - Maker: DeepSeek - Context window: 262.1K · 1M tokens - Input price: $0.047 to $0.690 per million tokens - Output price: $0.174 to $2.050 per million tokens - Providers: 7 independent providers - Regions: eu, global, uk, us, us-east ## Providers - [Munito AI](https://liquidinference.ai/providers/9dcb5dfe-3784-4ceb-a295-97dbe47862e9.md): global, $0.047 input and $0.174 output per million tokens, $0.00094 cache read per million tokens, 1M tokens of context - [Valar](https://liquidinference.ai/providers/92f9e9e4-c371-44ab-87ae-d39c5ab2fee4.md): us-east, $0.048 input and $0.178 output per million tokens, $0.0048 cache read per million tokens, 1M tokens of context - [blackfuel](https://liquidinference.ai/providers/6201dfca-89d1-404c-a728-6042d8e62de7.md): global, $0.049 input and $0.196 output per million tokens, $0.0098 cache read per million tokens, 1M tokens of context - [Boundless](https://liquidinference.ai/providers/7cd637bc-bdb6-4571-9d77-ef0bff1f172f.md): us, $0.080 input and $0.350 output per million tokens, $0.0016 cache read per million tokens, 1M tokens of context - [umans-ai](https://liquidinference.ai/providers/40185d21-2eb6-4d33-b06e-7dc56c37bce4.md): uk, $0.150 input and $0.600 output per million tokens, $0.028 cache read per million tokens, 262.1K tokens of context - [EmpirioLabs AI](https://liquidinference.ai/providers/4f49f07c-0d26-44bd-88a8-34f3f5fbd3b7.md): global, $0.200 input and $0.800 output per million tokens, $0.020 cache read per million tokens, 1M tokens of context - [SOKKAN](https://liquidinference.ai/providers/65502412-bcc7-4baa-9a9a-e20ea20a38d4.md): eu, $0.690 input and $2.050 output per million tokens, $0.140 cache read per million tokens, 262.1K tokens of context ## Scores - Intelligence: 32.6, #13 of 41 - HLE: 43.3, #23 of 273 - AA-LCR: 82.7, #21 of 237 - SciCode: 55.9, #23 of 123 Scores: Artificial Analysis (https://artificialanalysis.ai/) ## Request ```sh curl https://router.inference.ai.exchange/v1/chat/completions \ -H "Authorization: Bearer $LIQUID_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "deepseek-v4.1-flash-1017", "messages": [{"role":"user","content":"Say hello."}] }' ``` ## Questions ### What is DeepSeek V4.1 Flash 1017? DeepSeek V4.1 Flash 1017 is a model from DeepSeek. ### How much does DeepSeek V4.1 Flash 1017 cost? Offers now ask $0.047 to $0.690 per million input tokens and $0.174 to $2.050 per million output tokens. A job pays for the tokens it uses. The exchange picks the cheapest eligible offer. ### What is the context length of DeepSeek V4.1 Flash 1017? The largest offer takes 1,048,576 input tokens. A smaller offer can take less. The exchange skips an offer that cannot take your message. ### What can DeepSeek V4.1 Flash 1017 do? Its providers list Vision, Reasoning budget, Reasoning effort, JSON object, JSON schema, Frequency penalty, Logit bias, Log probabilities, Min-p sampling, Presence penalty, Repetition penalty, Seed, Stop sequences, Top-k sampling, Top-p sampling, Text, Tools. ### What inputs and outputs does DeepSeek V4.1 Flash 1017 support? Text · Images → Text. ### Which providers serve DeepSeek V4.1 Flash 1017? 7 independent providers quote it now, with 7 offers. The table above ranks them by the cost of a typical job. ### How do I call DeepSeek V4.1 Flash 1017? Send "deepseek-v4.1-flash-1017" as the model in an OpenAI or Anthropic request. The API section links to setup steps for each client. ### When was DeepSeek V4.1 Flash 1017 listed? The exchange first listed it on 10/17/2026. This is not its release date. ## Related pages - [This page in a browser](https://liquidinference.ai/models/deepseek-v4.1-flash-1017) - [DeepSeek V4 Flash 0731](https://liquidinference.ai/models/deepseek-v4-flash-0731.md) - [DeepSeek V4 Flash](https://liquidinference.ai/models/deepseek-v4-flash.md) - [DeepSeek V4.1 Flash](https://liquidinference.ai/models/deepseek-v4.1-flash.md) - [DeepSeek V4.1 Flash:thinking](https://liquidinference.ai/models/deepseek-v4.1-flash%3Athinking.md) - [DeepSeek V4.1 Flash 1017:thinking](https://liquidinference.ai/models/deepseek-v4.1-flash-1017%3Athinking.md) - [DeepSeek V4 Flash 0731:thinking](https://liquidinference.ai/models/deepseek-v4-flash-0731%3Athinking.md) - [Set up a client](https://liquidinference.ai/connect/deepseek-v4.1-flash-1017) - [All models](https://liquidinference.ai/models) - [Providers](https://liquidinference.ai/providers.md) - [Discover the best model for your budget](https://liquidinference.ai/discover) - [Quickstart](https://liquidinference.ai/docs/quickstart.md) - [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt) - [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)