Source: https://ailoot.ai/models/en/k3-1-pro-highspeed/ Canonical: https://ailoot.ai/models/en/k3-1-pro-highspeed/ Language: en # k3.1-pro-highspeed [Markdown](https://ailoot.ai/models/en/k3-1-pro-highspeed/index.md) · [JSON](https://ailoot.ai/models/en/k3-1-pro-highspeed/facts.json) ## [k3.1-pro-highspeed](https://ailoot.ai/models/en/k3-1-pro-highspeed/) `k3.1-pro-highspeed` MoonshotAITextInput $0.004 / 1KOutput $0.02 / 1K Kimi K3.1 Pro Highspeed is a distinct K3.1 Pro variant for text conversations, material analysis and code preparation through iterative work. Kimi K3.1 Pro Highspeed is a distinct K3.1 Pro variant that Moonshot AI introduced alongside the series’ main model. The developer presents it as a version focused on interaction speed. In Ailoot API, it has its own listing and the exact identifier `k3.1-pro-highspeed`, allowing you to select it separately from the regular K3.1 Pro. ### For iterative work Use this variant in a text workflow where the result is refined over several messages: first analyze the task, then choose an approach, and finally prepare usable text or code. For example, provide a program fragment and the desired behavior, receive a proposal, add constraints and ask for a specific section to be revised. Another use case is material analysis. Add excerpts from several documents, state your questions and ask for a brief conclusion followed by an explanation for each source. For a long discussion, retain the goal, accepted decisions and open questions so that the next response has a clear foundation. ### What to include in a request - The task and output type: an explanation, plan, program code or analytical text. - Source data with section names and their order of priority. - Constraints to consider when preparing the response. - Verification criteria: which conditions must hold and which details must be explained. You can ask for a comparison of options, step-by-step instructions or an explanation of a code change. For calculations, specify the units and source values; for a report, state the audience, structure and length. These details make the result easier to use in subsequent work. ### Format and size The listing accepts text input and returns text. You can supply instructions, conversation history, documents in text form and code. Standard has limits of up to 262,144 input tokens and 65,536 response tokens. Account for history and supplied material when composing a large request. For substantial work, establish an overall plan, then examine individual parts in sequence and retain intermediate conclusions. ### Available through Ailoot API Input types `text` Output types `text` Context 262,144 *tokens* Max. output 65,536 *tokens* Input $0.004 */ 1K* Output $0.02 */ 1K* Cache read $0.0002 */ 1K* Cache write $0.004 */ 1K* Cache write, 5 min $0.004 */ 1K tokens* Input types `text` Output types `text` Context 262,144 *tokens* Max. output 65,536 *tokens* Input $0.004 */ 1K* Output $0.02 */ 1K* Cache read $0.0002 */ 1K* Cache write $0.004 */ 1K* Cache write, 5 min $0.004 */ 1K tokens* Input types `text` Output types `text` Context 262,144 *tokens* Max. output 65,536 *tokens* Input $0.004 */ 1K* Output $0.02 */ 1K* Cache read $0.0002 */ 1K* Cache write $0.004 */ 1K* Cache write, 5 min $0.004 */ 1K tokens* Input types `text` Output types `text` Context 262,144 *tokens* Max. output 65,536 *tokens* Input $0.004 */ 1K* Output $0.02 */ 1K* Cache read $0.0002 */ 1K* Cache write $0.004 */ 1K* Cache write, 5 min $0.004 */ 1K tokens* `k3.1-pro-highspeed` · JSON ``` {"about":"Kimi K3.1 Pro Highspeed is a distinct K3.1 Pro variant that Moonshot AI introduced alongside the series’ main model. The developer presents it as a version focused on interaction speed. In Ailoot API, it has its own listing and the exact identifier `k3.1-pro-highspeed`, allowing you to select it separately from the regular K3.1 Pro.\n\n### For iterative work\n\nUse this variant in a text workflow where the result is refined over several messages: first analyze the task, then choose an approach, and finally prepare usable text or code. For example, provide a program fragment and the desired behavior, receive a proposal, add constraints and ask for a specific section to be revised.\n\nAnother use case is material analysis. Add excerpts from several documents, state your questions and ask for a brief conclusion followed by an explanation for each source. For a long discussion, retain the goal, accepted decisions and open questions so that the next response has a clear foundation.\n\n### What to include in a request\n\n- The task and output type: an explanation, plan, program code or analytical text.\n- Source data with section names and their order of priority.\n- Constraints to consider when preparing the response.\n- Verification criteria: which conditions must hold and which details must be explained.\n\nYou can ask for a comparison of options, step-by-step instructions or an explanation of a code change. For calculations, specify the units and source values; for a report, state the audience, structure and length. These details make the result easier to use in subsequent work.\n\n### Format and size\n\nThe listing accepts text input and returns text. You can supply instructions, conversation history, documents in text form and code. Standard has limits of up to 262,144 input tokens and 65,536 response tokens. Account for history and supplied material when composing a large request. For substantial work, establish an overall plan, then examine individual parts in sequence and retain intermediate conclusions.","alias_of":null,"aliases":[],"author":"MoonshotAI","canonical_model":"k3.1-pro-highspeed","ctx":262144,"formats":["chat","gemini","messages","responses"],"id":"k3.1-pro-highspeed","input":["text"],"kind":"text","max_out":65536,"methods":[{"cache_read":0.2,"cache_write":4.0,"cache_write_1h":null,"cache_write_5m":4.0,"conditional_meter":null,"ctx":262144,"family":"anthropic","fast_multiplier":null,"flex_multiplier":null,"fmt":"messages","http":"POST","img_in":null,"img_out":null,"in":4.0,"input":["text"],"label":"Anthropic Messages","max_out":65536,"max_tool_calls":null,"out":20.0,"output":["text"],"path":"/v1/messages","request_model_id":"k3.1-pro-highspeed","route_label":"Core","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.2,"cache_write":4.0,"cache_write_1h":null,"cache_write_5m":4.0,"conditional_meter":null,"ctx":262144,"family":"openai","fast_multiplier":null,"flex_multiplier":null,"fmt":"responses","http":"POST","img_in":null,"img_out":null,"in":4.0,"input":["text"],"label":"OpenAI Responses","max_out":65536,"max_tool_calls":null,"out":20.0,"output":["text"],"path":"/v1/responses","request_model_id":"k3.1-pro-highspeed","route_label":"Core","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.2,"cache_write":4.0,"cache_write_1h":null,"cache_write_5m":4.0,"conditional_meter":null,"ctx":262144,"family":"openai","fast_multiplier":null,"flex_multiplier":null,"fmt":"chat","http":"POST","img_in":null,"img_out":null,"in":4.0,"input":["text"],"label":"OpenAI Chat","max_out":65536,"max_tool_calls":null,"out":20.0,"output":["text"],"path":"/v1/chat/completions","request_model_id":"k3.1-pro-highspeed","route_label":"Core","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.2,"cache_write":4.0,"cache_write_1h":null,"cache_write_5m":4.0,"conditional_meter":null,"ctx":262144,"family":"gemini","fast_multiplier":null,"flex_multiplier":null,"fmt":"gemini","http":"POST","img_in":null,"img_out":null,"in":4.0,"input":["text"],"label":"Gemini generateContent","max_out":65536,"max_tool_calls":null,"out":20.0,"output":["text"],"path":"/v1beta/models/{model}:generateContent","request_model_id":"k3.1-pro-highspeed","route_label":"Core","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]}],"model_aliases":[{"canonical_model_id":"k3.1-pro-highspeed","request_model_id":"k3.1-pro-highspeed","route_label":"Core"}],"name":"k3.1-pro-highspeed","price":{"in":4.0,"in_label":null,"out":20.0,"out_label":null,"sort_in":4.0,"sort_out":20.0,"varies":false},"public_id":"k3.1-pro-highspeed","short":"Kimi K3.1 Pro Highspeed is a distinct K3.1 Pro variant for text conversations, material analysis and code preparation through iterative work."} ``` ## Questions How do I choose a model for my task? First identify the required input and output: text, image, audio or video. Then compare compatible API methods, the exact model ID or current alias target, price and billing unit. GET /v1/models is free and lists models available to your key. Does each model support every API method and media type? Use the API methods and input/output types listed on the model card. Support for text, images, audio or video depends on the selected model and method; check their request example before sending your data. What is the difference between a model ID and an alias? An exact model ID names a specific model. An alias points to a model and its target can change. Check the current alias target in the catalogue; use the exact ID when your integration needs a specific model. How do I compare prices before sending a request? Check the model card for the price and billing unit of the selected API method. Compare the same unit and input/output type; request history shows actual usage and the charged amount. What does a subscription give me? A discount on token purchases for regular use. Choose a plan for your request volume; subscription terms and pricing are shown at checkout. How do I apply a promo code for up to 50% off? Enter the promo code when buying tokens. The total updates according to the promotion terms; you can see the discount before paying. ## Ailoot · The company and its project portfolio Ailoot combines established operating experience, a large client base, stable service and ongoing KPI control. The company and its project portfolio: millions of customers; monthly sales in the billions. Ailoot brings that operating experience to API access for AI features in customer products, agents, applications and automations.