Pareto 26.10

{"about":"### Pareto 26.10 如何運作\n\nPareto 26.10 是 Unbiased 複合模型的穩定版本。其方式是為每次請求選擇數個先進模型與開放模型，再將結果整合成一個答案。這與只把問題轉交給單一選定模型不同：使用者面對的是一個 Pareto，取得的是整合結果。參與的模型組合可能改變，因此版本名稱並不代表固定的基礎模型清單。\n\n### Ailoot 的文字處理\n\n在 Ailoot，Pareto 26.10 接受文字並傳回文字。此連線的上下文視窗為 1,048,576 個 token，包含指示、對話歷史、傳入資料及生成中的答案。模型中繼資料標示的答案容量最多為 131,072 個 token；這是上限，並非每次生成的必要長度。為了有效工作，適合預先指定輸出篇幅與章節順序。\n\n長上下文可在一個請求中比對多份文字資料：技術需求與實作、需求與討論紀錄，或文件的數個版本。請以清楚名稱提供原始片段，並要求結論對應至各片段。例如，可建立差異表、找出需求矛盾，或根據整組資料準備修改計畫。這些是文字任務的表達方式；存取檔案或外部系統的能力由應用程式決定。\n\n### 如何建立實用請求\n\n分析程式碼時，加入相關函式、預期行為與觀察到的錯誤。要求先解釋它們之間的關係，再提出局部修改與驗證方法。研究提供的文字時，請提出問題、在請求內列出來源，並指定哪些主張必須註明對應片段。準備文件時，請說明讀者、用途、必要章節與驗收標準。\n\n文字連線提供 Messages、Responses、Chat Completions 及文字 generateContent 方法。選擇格式有助於整合至現有客戶端，本身不會新增影像閱讀、網路搜尋或命令執行。取得的程式碼、計畫與建議仍是文字生成結果，後續行動需由應用程式執行。\n\n### 明確固定版本選擇\n\n識別碼 `unbiased/pareto-26.10` 選取的就是 26.10 版本。需要在應用程式設定中明確固定模型，或使用自有任務集比較同一版本結果時，這很實用。26.9 是獨立版本，並有自己的上下文視窗。","alias_of":null,"aliases":[],"author":"Unbiased","canonical_model":"unbiased/pareto-26.10","ctx":null,"formats":["chat","gemini","messages","responses"],"id":"unbiased/pareto-26.10","input":["text"],"kind":"text","max_out":null,"methods":[{"cache_read":0.06,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"anthropic","fast_multiplier":1,"flex_multiplier":1,"fmt":"messages","http":"POST","img_in":null,"img_out":null,"in":1.6,"input":["text"],"label":"Anthropic Messages","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1/messages","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.06,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"openai","fast_multiplier":1,"flex_multiplier":1,"fmt":"responses","http":"POST","img_in":null,"img_out":null,"in":1.6,"input":["text"],"label":"OpenAI Responses","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1/responses","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.06,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"openai","fast_multiplier":1,"flex_multiplier":1,"fmt":"chat","http":"POST","img_in":null,"img_out":null,"in":1.6,"input":["text"],"label":"OpenAI Chat","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1/chat/completions","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]},{"cache_read":0.06,"cache_write":null,"cache_write_1h":null,"cache_write_5m":null,"conditional_meter":null,"ctx":null,"family":"gemini","fast_multiplier":1,"flex_multiplier":1,"fmt":"gemini","http":"POST","img_in":null,"img_out":null,"in":1.6,"input":["text"],"label":"Gemini generateContent","max_out":null,"max_tool_calls":null,"out":6.4,"output":["text"],"path":"/v1beta/models/unbiased/pareto-26.10:generateContent","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra","status_reads":[],"tiers":[],"tool_prices":null,"unit":"token","units":[]}],"model_aliases":[{"canonical_model_id":"unbiased/pareto-26.10","request_model_id":"unbiased/pareto-26.10","route_label":"Ultra"}],"name":"Pareto 26.10","price":{"in":1.6,"in_label":null,"out":6.4,"out_label":null,"sort_in":1.6,"sort_out":6.4,"varies":false},"public_id":"unbiased/pareto-26.10","short":"Unbiased 的複合文字模型，上下文為 1,048,576 個 token，適合分析大型資料集並準備詳盡答案。"}