API Hop

Kimi K3 API:價格與文字整合

查看 Kimi K3 Token 價格與程式設計、文件分析的 Chat Completions 範例。請確認支援輸入、推理行為及整合限制。

Kimi K3 API 價格與計費

官方價格

輸入
$3.0000 /M
輸出
$15.0000 /M
快取輸入
$0.3000 /M

API Hop 價格 降低 30%

輸入
$2.1000 /M
輸出
$10.5000 /M
快取輸入
$0.2100 /M

參考價格尚未經獨立驗證。比較成本前,請確認來源最新的價格、計費單位和適用條件。

Kimi K3 線上聊天工具

模型設定

進階參數
0 個字元起(0/無固定上限)
無固定字元上限;完整請求仍受請求大小和模型上下文限制。此處不是 Token 計數。
0 – 2
0 – 1
-2 – 2
-2 – 2

對話

今天有什麼可以幫你?

就緒

重設並開始新的對話?

這將清空目前對話和未傳送的內容,並還原預設參數。

API Hop 實測範例

2026 年 10 月 22 日透過 API Hop 記錄。每個結果僅代表所列模型與模式的一次請求,不保證成功率、速度或正式環境品質。下方模型回答保留原始語言。

附段落引用的發布決策

kimi-k3 · document-citations ·

原文節錄

**Answer summary:** Production release is **not approved**. Staging established only export-formatting/export v7 verification — nothing about production. **Mei** owns the remaining duplicate-delivery tests; documentation ownership is **unassigned**.
完整模型回答(未修改)
**Answer summary:** Production release is **not approved**. Staging established only export-formatting/export v7 verification — nothing about production. **Mei** owns the remaining duplicate-delivery tests; documentation ownership is **unassigned**.

| Conclusion | Exact supporting quote | Paragraph ID | Uncertainty |
|---|---|---|---|
| Production release is not approved; approval was withheld pending tests | "the release reviewer withheld production approval until duplicate-delivery tests pass" | P31 | Low — explicit statement |
| No approval or completed test recorded later (cross-check of P04's Friday shipping proposal, which "was not an approval") | "No completed test result or production approval is recorded in this document." | P36 | Low — explicit; P04 proposal superseded by P31/P36 |
| Staging established export formatting checks passed (repeated across components), and verified export v7 on synthetic data only | "staging verified export version 7 with three synthetic records. Production deployment and billing checks were not performed." | P18 | Low for staging result; production readiness not established |
| Staging did not measure production latency, charges, or customer outcomes | "no production latency, charge or customer outcome was measured" | P01 (and P02–P03, P05–P17, P19–P30, P32–P35, identical wording) | Low — explicit; applies to all component entries |
| Remaining duplicate-delivery tests are owned by Mei | "Mei owns those tests." | P31 | Low — explicit; tests scheduled, not completed ("Mei scheduled duplicate-delivery tests for October 16," P36) |
| Documentation has no owner; a documentation check was only planned | "Documentation ownership remains unassigned." | P31 (earlier: "Documentation ownership was still unassigned," P04) | Low that it is unassigned as of this document; future owner unknown. Note: component entries say "The named reviewer will check documentation next week" (e.g., P01), but no name is given and no completion is recorded |

**Unresolved questions:**
1. Did the duplicate-delivery tests scheduled for October 16 (P36) pass, and has the release reviewer since granted production approval?
2. Who will be assigned documentation ownership, and did the unnamed "named reviewer" ever complete the documentation check promised for "next week" (P01 et al.)?

文件為合成樣本,並非最大上下文測試。結論與輸入一致,但兩處輔助引文將句尾句點改為逗號:P36 的測試排程引文與 P04 的文件歸屬引文。這些標點並非逐字保留,仍需人工核對引用。

完整請求與輸入資料

POST /v1/chat-completions

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      "content": "Use only the following synthetic document. Answer: Is production release approved? What did staging establish? Who owns the remaining tests and documentation? Return a compact table of conclusion, exact supporting quote, paragraph ID and uncertainty, followed by two unresolved questions. Cross-check proposals against later updates; never infer a completed test or production success. Keep the answer under 500 words. This sample tests citation accuracy on this document, not maximum context length.\n\n[P01] Component 1 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P02] Component 2 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P03] Component 3 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P04] On October 10, the release coordinator proposed shipping export version 7 on Friday. The proposal was not an approval. Documentation ownership was still unassigned.\n\n[P05] Component 5 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P06] Component 6 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P07] Component 7 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P08] Component 8 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P09] Component 9 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P10] Component 10 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P11] Component 11 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P12] Component 12 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P13] Component 13 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P14] Component 14 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P15] Component 15 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P16] Component 16 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P17] Component 17 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P18] On October 11, staging verified export version 7 with three synthetic records. Production deployment and billing checks were not performed.\n\n[P19] Component 19 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P20] Component 20 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P21] Component 21 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P22] Component 22 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P23] Component 23 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P24] Component 24 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P25] Component 25 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P26] Component 26 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P27] Component 27 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P28] Component 28 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P29] Component 29 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P30] Component 30 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P31] On October 12, the release reviewer withheld production approval until duplicate-delivery tests pass. Mei owns those tests. Documentation ownership remains unassigned.\n\n[P32] Component 32 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P33] Component 33 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P34] Component 34 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P35] Component 35 review: staging checks passed for export formatting. Production rollout has not been approved by this entry. The named reviewer will check documentation next week; no production latency, charge or customer outcome was measured. This paragraph records a proposed review, not completion.\n\n[P36] On October 13, Mei scheduled duplicate-delivery tests for October 16. No completed test result or production approval is recorded in this document."
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回應中繼資料與回報用量
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下載公開證據紀錄

Kimi K3 提示詞範例

這些是 Kimi K3 的評估提示詞,並非模型實測輸出。僅分析提供的文字,不執行程式碼、不檢查正式環境系統,也不證明長上下文效能。請核對引用證據與驗收條件,並在正式使用前檢查回應中繼資料與用量。

僅使用這份文件樣本:[P1] 匯出修復通過預備環境檢查。[P2] 有人提議週五發布,但未獲核准。[P3] Mei 將於週二審核錯誤訊息。[P4] 文件尚無負責人。以表格回傳結論、準確引文、段落編號和不確定性。正式發布是否已核准?誰負責文件?缺失事實標為未知。引文必須與樣本一致,不由預備環境成功推斷正式環境成功。這個小樣本不測試最大上下文長度。

將合成記錄擷取為含 id、owner、deadline、evidence 的 JSON:[R1] 問題 41:Ana 負責匯出修復;未約定期限。[R2] 問題 42:審核期限 10 月 15 日;未指定負責人、未說明年份。缺失值用 null,保留原文不完整日期。evidence 引用原文,不猜測年份或負責人。逐欄核對來源;這只是文字整理,不是資料庫操作。

虛構的兩人團隊每天執行 2,000 份報告,允許 30 分鐘內完成。已有資料庫,沒有佇列服務;任務須在重啟後恢復並避免重複傳送。比較資料庫批次處理與獨立佇列,提供決策表、有條件的建議、三個未知項及一個會改變選擇的條件。不要編造基準、成本或已驗證的保證。

什麼是 Kimi K3

面向長流程程式設計與知識工作的原生多模態模型

我們將 Kimi K3 定位為面向複雜任務的推理與 Agent 模型,重點關注需要持續理解上下文、呼叫工具並根據結果修正方案的工作場景。它由 Moonshot AI 開發,是多模態模型,具備原生視覺能力,可以理解文字、圖片和影片,適用方向包括專案程式設計、資料研究和多步驟知識工作。

它的多模態能力能夠擴充套件它的應用場景,比如圖片理解/OCR,它和傳統OCR方案相比的優點在於,你不需要單獨訓練模型,就能夠有比較好的理解能力。

支援百萬 Token 上下文的開放權重 MoE 模型

Kimi K3 採用混合專家架構,也就是 MoE,總參數為 2.8 萬億,每個 Token 啟用約 1040 億參數,模型上下文視窗為 1,048,576 Token。官方已經開放完整模型權重,採用 Kimi K3 License。

我們認為,百萬 Token 上下文的實際價值,在於可以把更多相關資料放進同一次分析,例如專案規範、多個模組的程式碼和歷史討論。對於有自主部署需求的團隊,開放權重也給部分企業和使用者提供了自部署的場景。

始終開啟思考,支援三檔推理強度

Kimi K3 始終進行思考。當前 Kimi 官方 API 通過 reasoning_effort 提供 low、high、max 三檔推理強度,預設使用 max。

我們建議根據任務難度安排推理預算:簡單分類和資料提取可以先使用 low,多步驟分析可以從 high 開始,需要反覆檢查約束的複雜任務再比較 max。我們從其他從模型的測試經驗來看,max的綜合收益並不一定是最高的,所以要結合場景來做測試和判斷。

RequestBeam 的 Kimi K3 線上工具與 API

我們希望通過 RequestBeam,讓你更快地瞭解 Kimi K3 在自己任務中的真實表現。你只需要登入、建立 API Key,並完成少量儲值,就可以通過線上工具開始體驗,無需先編寫 API 對接程式碼,也不必為了短期評估購買固定方案。

Kimi K3 的核心功能與領域優勢

長週期軟體開發:從理解需求到修復問題、執行測試

我們認為,長週期程式設計是 Kimi K3 最值得優先測試的能力。它可以在 Agent 框架提供檔案、終端和測試工具的情況下,連續完成程式碼閱讀、方案修改、測試執行和問題修復,而不只是根據一句需求生成一段程式碼。

在我們收集的客戶的使用分享中,有使用者提到,Kimi K3 幫助他繼續推進了此前停滯的專案,並完成多個連續開發階段。也有開發者表示,它在跨檔案分析和尋找模組關係方面表現不錯,但第一次提出的修改方案不一定安全,有時還會引入新的問題。

我們覺得,這恰好說明了 Kimi K3 在真實開發中的使用方式:不要只讓模型“幫我們修復這個 BUG”,而是提供明確的測試用例、不能改變的既有行為,以及允許修改的檔案範圍。

對於後端重構、複雜資料處理和生產環境程式碼,我們建議讓它先解釋修改計劃,再執行修改,最後通過自動化測試確認結果。即使模型已經報告任務完成,也不應跳過程式碼審查。

視覺化開發:結合介面截圖持續最佳化前端與互動效果

Kimi K3 的視覺理解能力,使它能夠將介面截圖、設計要求和程式碼放在同一任務中處理。

例如,我們可以先讓模型根據參考圖片生成網頁,再通過瀏覽器工具獲取實際渲染截圖,讓模型比較頁面與設計稿之間的差異,繼續調整佈局、顏色、字型和互動細節。

在我們的客戶群回饋中,有使用者對 Kimi K3 的前端、視覺化專案和小遊戲製作給出了積極評價。

我們認為,Kimi K3 比較適合產品原型、活動頁面、視覺化儀表盤和需要反覆對照截圖的開發任務。尤其是獨立開發者,可以先用它生成可執行的版本,再逐步完善頁面體驗。

Agent 工具協作:執行多步驟任務,需要給於明確的邊界

Kimi K3 可以配合外部工具進行檔案讀寫、終端操作、資料檢索以及多步驟自動化工作。模型負責判斷下一步行動,實際工具呼叫和執行環境則由應用程式或 Agent 框架提供。

我們特別關注一個現象:同一個模型放在不同 Agent 框架中,最終任務完成率可能有明顯差異。

此外,Moonshot AI 官方也提醒,Kimi K3 可能在使用者意圖不明確時主動做出超出預期的決定。因此,在需要嚴格控制行為的任務中,我們建議通過系統提示詞或 AGENTS.md 明確操作權限。

Kimi K3 基準測試與效能表現

我們在這一部分分別使用 Moonshot 的釋出期官方測試,以及截至 2026 年 10 月 7 日可查的 Artificial Analysis 獨立評測。下述官方 Kimi K3 成績均採用 max 思考強度;我們同時保留基準版本和關鍵測試條件,方便你判斷它們與實際任務的關係。

軟體工程:DeepSWE 67.5%,ProgramBench 77.8%

Moonshot 公佈的 Kimi K3 成績中,DeepSWE v1.1 為 67.5%,ProgramBench 為 77.8%,這兩項 K3 測試使用 Kimi Code 框架。我們把它們作為模型處理程式碼倉庫任務與持續程式設計工作的參考。

對於準備接入程式設計助手的團隊,我們建議分別測試已有問題修復、小功能開發和小型專案實現。評估重點可以放在一次完成率、失敗後的修正能力,以及最終程式碼需要多少人工返工。這樣的結果更容易對應到開發成本。

終端任務:Terminal-Bench 2.1 與 4.0 需要分別解讀

官方釋出期測試中,Kimi K3 配合 Kimi Code,在 Terminal-Bench 2.1 上取得 88.3%。當前 Artificial Analysis 的 Terminal-Bench 4.0 測試中,K3 Max 的成績約為 13%。

兩組結果對應不同任務集和執行框架。AA 的 4.0 測試包含 66 個更難的終端任務,使用 mini-swe-agent,並對每個任務重複三次。在實際業務場景中,我們建議你使用其他harness進行測試。

研究與工具呼叫:BrowseComp 91.2%,MCPMark-Verified 94.5%

官方報告中,Kimi K3 的 BrowseComp 成績為 91.2%,MCPMark-Verified 為 94.5%。其中 BrowseComp 的 91.2% 使用了在 300K Token 時觸發上下文壓縮的策略;直接使用 1M 上下文且不進行上下文管理時,成績為 90.4%。

我們認為,這組結果說明,研究和工具協這塊是 Kimi K3 的強項,同時也提醒我們關注應用如何管理上下文,從我們的經驗來看,上下文管理對於實際效果的影響會很大。

長文推理:AA-LCR v1.1 達到 88.7%

Artificial Analysis 的 AA-LCR v1.1 專項頁面記錄,Kimi K3 Max 的成績為 88.7%。這項評測包含 100 道需要綜合長文件資訊的問題,涉及公司報告、論文和行業資料等內容;文件長度約為 1 萬至 10 萬 Token。

我們將這項結果視為 Kimi K3 跨資料分析能力較有說服力的證據。對於接近百萬 Token 的實際輸入,我們仍建議單獨測試,按照我們以往的測試經驗來看,如果輸入貼近模型允許的上限,它的輸出並不會特別好。

綜合指數與響應速度:44 分,輸出約 45 Token/秒

Artificial Analysis Intelligence Index v4.3.2 將 Kimi K3 Max 記為 44 分。其輸出速度約為每秒 45 Token,首個 Token 約需 3.92 秒,計入思考後首個答案 Token 約需 48.58 秒。

我們會分別檢測開始返回資料、出現正式答案和整個任務完成的時間。對於互動頻繁的功能,這些時間會影響使用者的使用體驗,對於複雜分析,則需要結合業務場景的結果品質判斷。

Kimi K3 與 DeepSeek V4 Pro、V4.1 Flash、Claude Fable 5.1、GPT-5.6 Sol 同類模型對比

我們使用 Artificial Analysis v4.3.2 的同版本資料進行比較。以下均為 Max 檔位;Claude Fable 5.1 保留評測頁標註的 Default Fallback 配置。AA-LCR 在比較頁中以整數百分比顯示,因此 Kimi K3 的 88.7% 顯示為 89%。

表中的任務成本是 AA 按評測權重計算的平均成本,包含輸入、快取、思考和答案等用量,供模型選型參考;RequestBeam 的實際費用按平台價格與請求用量計算。成本口徑說明

模型與測試檔位綜合指數AA-LCR v1.1加權單任務成本
Kimi K3 Max4489%$2.00
DeepSeek V4 Pro 0813 Max3680%$0.67
DeepSeek V4.1 Flash Max3984%$0.27
Claude Fable 5.1 Max,Default Fallback5385%$7.63
GPT-5.6 Sol Max4784%$1.99
Artificial Analysis v4.3.2 2026-10-07 · 所有模型均為 Max
智慧指數 分數 · 越高越好
  • Kimi K3 Max 44
  • DeepSeek V4 Pro 0813 Max 36
  • DeepSeek V4.1 Flash Max 39
  • Claude Fable 5.1 Max預設備援設定 53
  • GPT-5.6 Sol Max 47
AA-LCR v1.1 百分比 · 越高越好
  • Kimi K3 Max 89%
  • DeepSeek V4 Pro 0813 Max 80%
  • DeepSeek V4.1 Flash Max 84%
  • Claude Fable 5.1 Max預設備援設定 85%
  • GPT-5.6 Sol Max 84%
加權單任務成本 USD/任務 · 越低越好
  • Kimi K3 Max $2.00
  • DeepSeek V4 Pro 0813 Max $0.67
  • DeepSeek V4.1 Flash Max $0.27
  • Claude Fable 5.1 Max預設備援設定 $7.63
  • GPT-5.6 Sol Max $1.99
AA-LCR 四捨五入:Kimi K3 88.7% → 89%。 AA 任務成本包含輸入、快取、推理與回答;不是 API Hop 價格。

資料來源:V4 Pro 對比、V4.1 Flash 對比、Fable 5.1 對比、GPT-5.6 Sol 對比。

對比 DeepSeek V4 Pro:長文分析表現更強,評測任務成本更高

在這組評測中,Kimi K3 的綜合指數、長文推理與知識工作成績高於 DeepSeek V4 Pro 0813。我們會優先把 K3 用於資料之間聯絡較複雜、需要綜合多種證據的任務,並檢查這種能力差異是否能減少人工整理和複核的時間。AA 同口徑對比

對於大量重複、驗收標準清楚的文字任務,我們也會測試 V4 Pro。它在這套評測中的任務成本更低;如果輸出已經達到業務要求,成本差異就可能成為擴大使用規模時的重要因素。

對比 DeepSeek V4.1 Flash:綜合與長文佔優,自動化任務另有取捨

Kimi K3 在綜合指數與 AA-LCR 上領先,但在 AutomationBench-AA 中,V4.1 Flash 為 69%,K3 為 58%;在 Terminal-Bench 4.0 中,兩者分別為 27% 和 13%。我們認為,這說明不同任務型別會改變模型排序。AA 同口徑對比

如果應用主要處理長資料分析,我們建議重點比較 K3;如果任務集中在流程自動化、終端操作和高頻呼叫,我們會把 V4.1 Flash 列為重要候選,並同時比較成功率與完整執行成本。

對比 Claude Fable 5.1:終端程式設計存在差距,長文任務值得單獨比較

在上述 Default Fallback 配置下,Claude Fable 5.1 的綜合指數為 53,Kimi K3 為 44;Terminal-Bench 4.0 分別為 52% 和 13%。我們會把 Fable 5.1 作為複雜終端程式設計的重要對照。K3 則在 AA-LCR v1.1 上取得更高的成績,並具有更低的評測任務成本。AA 同口徑對比

對於閱讀多份資料後回答明確問題的應用,我們建議單獨測試 K3 的效果。對於需要持續操作終端、修復環境和完成工程驗證的任務,我們會更關注首次成功率與人工介入次數,再判斷額外模型費用是否值得。

對比 GPT-5.6 Sol:長文推理各有表現,完整任務成本接近

Kimi K3 的 AA-LCR 得分高於 GPT-5.6 Sol;GPT-5.6 Sol 的綜合指數和 Terminal-Bench 4.0 成績更高。我們尤其關注兩者的任務成本:在這套評測中分別約為 2.00 美元和 1.99 美元,已經十分接近。AA 同口徑對比

我們因此建議把完整任務跑完以後再比較費用,包括思考、工具互動、重試和最終答案。對於資料密集的分析工作,可以優先比較 K3;對於終端工程任務,可以把 GPT-5.6 Sol 作為重點對照,最後根據業務中的實際完成情況決定路由。

為什麼透過 API Hop 使用 Kimi K3?

依用量計費與模型成本最佳化

費用依目前 API Hop 費率與實際用量計算,可按需儲值。

統一 AI 模型與資料 API,一站存取多模型

一組 API 金鑰連接多個 AI 模型與資料服務,減少整合成本並可一鍵切換。業務應用同時需要 AI 與資料。

呼叫紀錄與應用程式存取控制,每次呼叫清楚可查

每次 API 呼叫都記錄在控制台中。可為不同應用程式建立獨立 API 金鑰。

依任務評估輸出

透過 API Hop 使用文件列出的模型 ID 與支援參數。依自己的驗收條件評估輸出,在正式使用前檢查用量紀錄與回應中繼資料。模型名稱或範例不保證每次結果。

如何在 API Hop 使用 Kimi K3

在控制台建立 API 金鑰後,請依文件開始使用 Kimi K3。

準備帳戶並線上測試

登入、確認餘額,然後建立 API 金鑰。

在試用區體驗

在試用區探索模型能力,找出最佳使用方式。

將 Kimi K3 整合至業務

依照開發者文件,將 Kimi K3 整合至業務。

後續模型升級

切換至新模型前,請先確認 API 金鑰的模型目錄回傳其精確 ID。若支援相同端點與請求欄位,再更新模型 ID,並在導入正式流量前測試回應格式、串流、輸出上限與計費。非同步圖片或影片任務還需驗證任務提交、狀態輪詢與結果取得。

Kimi K3 API 常見問題

通過 RequestBeam 呼叫 Kimi K3,介面地址和模型名稱怎麼填寫?

我們目前提供的 Kimi K3 接入地址是 POST https://api.requestbeam.com/v1/chat-completions,模型標識填寫 kimi-k3,認證使用 RequestBeam API Key。可以先按下面的最小請求確認接入,再逐項增加可選參數。RequestBeam Kimi API 文件

curl -X POST "https://api.requestbeam.com/v1/chat-completions" \
  -H "Authorization: Bearer $REQUESTBEAM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3",
    "messages": [
      {"role": "user", "content": "Organize this requirement into goals, constraints, and acceptance criteria: create an admin dashboard for internal employees with email login and password reset."}
    ],
    "stream": false
  }'

此 API Hop 模型使用統一的 Chat Completions 介面,不是 OpenAI Responses 或 Claude Messages。

Kimi K3 支援流式輸出和連續追問嗎?

我們提供流式和非流式兩種響應方式。設定 stream: true 時返回 SSE,設定 stream: false 或省略該欄位時返回完整 JSON。對於需要逐步展示結果的介面,我們建議使用流式響應。RequestBeam Kimi API 文件

連續追問需要應用按接入協議維護對話歷史,並在後續請求中攜帶相關上下文。線上工具中的 Memory 用來加入當前對話中可複用的歷史輪次;我們建議根據問題保留必要資料,並關注歷史增加帶來的輸入 Token 成本。線上工具的上下文說明

試用區記憶不會跨工作階段持續保留。停用後歷史仍可見,但不納入新請求。失敗、停止、截斷或不可重用回答不會加入正常歷史。

0

Kimi K3 支援百萬 Token 上下文,為什麼回答仍可能被截斷?

我們會先分別檢查上下文容量和輸出預算。RequestBeam 的 max_tokens 用於配置輸出額度,思考與最終答案共享這部分預算。額度太小時,即使還沒有輸出完整正文,也可能以 finish_reason: "length" 結束。RequestBeam 輸出預算說明

遇到 length 時,我們建議檢查是否給思考和答案留出了足夠空間,再決定增加預算或分步完成任務。如果報錯指向上下文超限,則需要精簡無關歷史和重複資料。

最後我們需要澄清一個觀點:百萬 token 上下文,不代表它真的能在百萬 token 級別返回好的結果,如果你追求結果的正確性,那麼控制上下文的長度目前為止是你唯一的選擇。

API 用戶端必須區分 reasoning_content 與最終 content。

0

呼叫 Kimi K3 時,400、401、402 和 429 分別怎麼處理?

我們建議先檢查 HTTP 狀態,再檢視響應中的數字 code。RequestBeam 的 Chat Completions 文件將常見錯誤定義如下。RequestBeam 錯誤響應文件

HTTP 狀態數字 code含義我們建議的處理方式
40010000請求無效檢查 model、messages、欄位型別與可選參數
40120000認證缺失或無效檢查 RequestBeam API Key 和 Bearer 認證頭
40240000可用餘額不足檢查賬戶餘額及本次請求需要的額度
42940001請求觸發限流降低併發和頻率,並採用退避重試

我們建議從最小請求開始排查,再逐項恢復參數。HTTP 狀態與響應中的 code 需要分別處理;如果問題持續出現,可以保留響應中的請求標識和相關參數,方便我們定位具體環節。

403 應檢查金鑰可見目錄中的模型權限。以完整錯誤回應診斷 502、503、504 及 SSE 串流內錯誤。

Kimi K3 試用區可以接受圖片、PDF 或影片嗎?

本頁提供文字對話,不含檔案或圖片上傳控制項。原生視覺理解需要支援該類輸入的介面。此工具不會下載連結檔案、讀取外部文件或自動搜尋網路。在此測試時,請先擷取相關文字。

一次請求可以回傳多個方案或保證有效 JSON 嗎?

Kimi K3 透過 API Hop 僅支援 n=1。請在單一回答中要求多個方案。對於 JSON,請定義欄位、型別與缺失值處理方式,再於應用程式中驗證語法、Schema 與業務意義。

相關文字 API