{"reference_analysis":{"provider":"Google LiteRT","checked_at":"2026-10-08","source_access":{"en":"Official project and developer sources reviewed; no provider API was called. Expected outputs below are our illustrative contracts, not measured results.","zh-TW":"已核對官方專案與開發來源；沒有呼叫供應商 API。下方預期輸出是本站示意契約，不是實測結果。"},"selection_basis":{"en":"Ten documented technical entry points, selected by task; not ten independent SDKs or an official ranking.","zh-TW":"依任務選出的十個有文件技術入口；不是十套獨立 SDK 或官方排名。"},"about_url":"https://developers.google.com/edge/litert","about":[{"label":{"en":"Project","zh-TW":"專案"},"value":{"en":"LiteRT is Google’s on-device model deployment framework, built on TensorFlow Lite.","zh-TW":"LiteRT 是 Google 建構於 TensorFlow Lite 基礎的裝置端模型部署框架。"}},{"label":{"en":"Scope","zh-TW":"範圍"},"value":{"en":"Covers model conversion, optimization and runtime execution across supported edge platforms.","zh-TW":"涵蓋支援邊緣平台上的模型轉換、最佳化與執行。"}},{"label":{"en":"Runtime choices","zh-TW":"執行選擇"},"value":{"en":"Current documentation distinguishes CompiledModel from the compatibility-oriented Interpreter path.","zh-TW":"現行文件區分 CompiledModel 與著重相容性的 Interpreter 路徑。"}},{"label":{"en":"Adjacent product","zh-TW":"相鄰產品"},"value":{"en":"LiteRT-LM adds language-model orchestration; it is a separate integration choice from this tensor inference example.","zh-TW":"LiteRT-LM 提供語言模型協調；其整合選擇與此張量推論範例不同。"}}],"items":[{"id":"overview","name":"CompiledModel quickstart","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/overview","audience":{"en":"ML application developers","zh-TW":"機器學習應用工程師"},"capability":{"en":"Prepare a model and use the on-device runtime.","zh-TW":"準備模型並使用裝置端執行環境。"},"io":{"en":"Compatible model and input tensors → output tensors.","zh-TW":"相容模型與輸入張量 → 輸出張量。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Output meaning comes from the model, not the runtime alone.","zh-TW":"輸出意義由模型定義，非執行環境自動提供。"},"validation":{"en":"Verify shapes, types and model-specific postprocessing.","zh-TW":"驗證形狀、型別與模型特定後處理。"}},{"id":"android","name":"Android integration","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/android","audience":{"en":"Android application teams","zh-TW":"Android 應用團隊"},"capability":{"en":"Select an Android runtime integration path.","zh-TW":"選擇 Android 執行環境整合路徑。"},"io":{"en":"Model, app and SDK configuration → device inference.","zh-TW":"模型、應用與 SDK 設定 → 裝置推論。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"API availability depends on the selected distribution and device.","zh-TW":"API 可用性取決於套件發行與裝置。"},"validation":{"en":"Test lifecycle and memory on the actual minimum target device.","zh-TW":"在最低目標裝置測試生命週期與記憶體。"}},{"id":"npu","name":"NPU acceleration","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/next/npu","audience":{"en":"Hardware optimization teams","zh-TW":"硬體最佳化團隊"},"capability":{"en":"Configure supported NPU execution.","zh-TW":"設定支援的 NPU 執行。"},"io":{"en":"Compatible graph and hardware → accelerated execution.","zh-TW":"相容運算圖與硬體 → 加速執行。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Not every operator or chip supports the same path.","zh-TW":"並非每個運算子或晶片支援相同路徑。"},"validation":{"en":"Record actual backend and compare numerical results to baseline.","zh-TW":"記錄實際後端並與基準比對數值。"}},{"id":"conversion","name":"Model conversion","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/conversion/overview","audience":{"en":"Model export engineers","zh-TW":"模型匯出工程師"},"capability":{"en":"Convert supported source models for LiteRT.","zh-TW":"轉換支援的來源模型供 LiteRT 使用。"},"io":{"en":"Source model → .tflite artifact.","zh-TW":"來源模型 → .tflite 產物。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"A successful export does not prove task quality.","zh-TW":"匯出成功不代表任務品質合格。"},"validation":{"en":"Compare source and exported model on held-out inputs.","zh-TW":"使用保留輸入比對來源與匯出模型。"}},{"id":"migration","name":"TensorFlow Lite migration","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/migration","audience":{"en":"Existing TFLite maintainers","zh-TW":"既有 TFLite 維護者"},"capability":{"en":"Review the supported migration paths to LiteRT.","zh-TW":"檢視轉移至 LiteRT 的支援路徑。"},"io":{"en":"Existing integration → selected updated runtime path.","zh-TW":"既有整合 → 選定更新後執行路徑。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Interpreter compatibility and CompiledModel adoption are different changes.","zh-TW":"Interpreter 相容與採用 CompiledModel 是不同變更。"},"validation":{"en":"Pin old and new dependencies and replay the same fixtures.","zh-TW":"固定新舊相依版本並回放同一樣本。"}},{"id":"optimization","name":"Model optimization","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/conversion/tensorflow/quantization/model_optimization","audience":{"en":"Model efficiency engineers","zh-TW":"模型效能工程師"},"capability":{"en":"Review optimization including post-training quantization.","zh-TW":"檢視包含訓練後量化的最佳化方法。"},"io":{"en":"Model and optional representative data → optimized artifact.","zh-TW":"模型與可能需要的代表資料 → 最佳化產物。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Quantization can change accuracy and tensor types.","zh-TW":"量化可能改變準確率與張量型別。"},"validation":{"en":"Measure quality drift before accepting any size or speed gain.","zh-TW":"接受體積或速度改善前量測品質漂移。"}},{"id":"cli","name":"LiteRT CLI installation","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/cli/installation","audience":{"en":"Build and tooling teams","zh-TW":"建置與工具團隊"},"capability":{"en":"Install command-line model tooling.","zh-TW":"安裝命令列模型工具。"},"io":{"en":"Supported environment and package → available CLI.","zh-TW":"支援環境與套件 → 可用 CLI。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Pin the tool version; installation alone is not deployment.","zh-TW":"固定工具版本；安裝完成不等於部署完成。"},"validation":{"en":"Record version and validate the chosen command on a fixture.","zh-TW":"記錄版本並以樣本驗證選定命令。"}},{"id":"microcontrollers","name":"Microcontroller runtime","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/microcontrollers/overview","audience":{"en":"Embedded firmware teams","zh-TW":"嵌入式韌體團隊"},"capability":{"en":"Run suitable small models in constrained environments.","zh-TW":"在資源有限環境執行適合的小模型。"},"io":{"en":"Supported model and firmware tensors → inference output.","zh-TW":"支援模型與韌體張量 → 推論輸出。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Memory and supported operations differ from desktop runtime.","zh-TW":"記憶體與支援運算不同於桌面環境。"},"validation":{"en":"Check tensor memory budget and target-board outputs.","zh-TW":"檢查張量記憶體預算與目標板輸出。"}},{"id":"cpp","name":"Prebuilt C++ SDK","kind":"API / SDK / developer guide","url":"https://developers.google.com/edge/litert/next/cpp_sdk","audience":{"en":"Native application developers","zh-TW":"原生應用工程師"},"capability":{"en":"Integrate prebuilt runtime libraries with CMake.","zh-TW":"透過 CMake 整合預編譯執行函式庫。"},"io":{"en":"Headers, libraries and model → native integration.","zh-TW":"標頭、函式庫與模型 → 原生整合。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Runtime and accelerator binaries must match platform and version.","zh-TW":"執行環境與加速二進位檔須符合平台與版本。"},"validation":{"en":"Verify loading and packaged dependencies on a clean target.","zh-TW":"在乾淨目標環境驗證載入與相依套件。"}},{"id":"source","name":"Source and release repository","kind":"API / SDK / developer guide","url":"https://github.com/google-ai-edge/LiteRT","audience":{"en":"Runtime maintainers","zh-TW":"執行環境維護者"},"capability":{"en":"Inspect source, releases and project build entry points.","zh-TW":"檢視原始碼、發行與專案建置入口。"},"io":{"en":"Pinned source revision → reproducible build inputs.","zh-TW":"固定來源修訂 → 可重現建置輸入。"},"runtime":{"en":"Selected LiteRT runtime and supported target hardware","zh-TW":"選定 LiteRT 執行環境與支援的目標硬體"},"constraint":{"en":"Repository head can differ from installed stable packages.","zh-TW":"儲存庫最新版本可能不同於已安裝穩定套件。"},"validation":{"en":"Record the exact tag or commit with build options.","zh-TW":"記錄精確標籤或提交與建置選項。"}}],"supporting_references":[{"id":"documentation","name":"Official documentation overview","url":"https://ai.google.dev/edge/litert","audience":{"en":"Developers and product owners selecting the supported technical path.","zh-TW":"選擇支援技術路徑的工程師與產品負責人。"},"validation":{"en":"Choose the operation, supported version and runtime before assigning implementation.","zh-TW":"安排實作前先選定操作、支援版本與執行環境。"}}]},"content_coverage":{"reference_guide":true,"developer_starter":false,"expected_results":true,"integration_test":"not-run","updated_at":"2026-10-08"},"developer_starter":{"version":"1.0.0","verification":"illustrative-contract-only;live-provider-not-run","filename":"LiteRT-expected-results.json","format":"json-example","scope":{"en":"Illustrative tensor inference contract. Tensor shape, dtype, normalization and labels must come from the actual model; no inference or benchmark was run.","zh-TW":"張量推論示意契約。張量形狀、型別、正規化與標籤須依實際模型定義；未執行推論或效能測試。"},"setup":{"en":"Review the scenarios below and map the actual SDK response into this internal contract. No credential, API call or live output is included. Replace example data only after your own integration test.","zh-TW":"先審閱下方情境，再將實際 SDK 回應對應至此內部契約。此處不含憑證、API 呼叫或真實輸出，示意資料須在自行串接測試後替換。"},"code":"{\n  \"schema_version\": \"1.0.0\",\n  \"example\": true,\n  \"provider\": \"Google LiteRT\",\n  \"status\": \"ok\",\n  \"input_id\": \"sample-001\",\n  \"data\": {\n    \"model_id\": \"example-model\",\n    \"backend\": \"example-cpu\",\n    \"outputs\": [\n      {\n        \"name\": \"example_scores\",\n        \"shape\": [\n          1,\n          3\n        ],\n        \"dtype\": \"float32\",\n        \"values\": [\n          [\n            0.1,\n            0.7,\n            0.2\n          ]\n        ]\n      }\n    ],\n    \"latency_ms\": null\n  },\n  \"error\": null,\n  \"verification\": \"illustrative-only;not-provider-response\"\n}","expected_results":[{"scenario":{"en":"Valid inference contract","zh-TW":"有效推論契約"},"input":{"en":"Pinned model; tensor shape and type match its signature.","zh-TW":"固定模型；張量形狀與型別符合簽章。"},"output":{"en":"ok; output tensor metadata and illustrative values.","zh-TW":"ok；輸出張量資訊與示意數值。"},"acceptance":{"en":"Compare to a trusted model fixture using agreed tolerances.","zh-TW":"使用約定誤差範圍與可信模型樣本比對。"}},{"scenario":{"en":"Empty application result","zh-TW":"應用空結果"},"input":{"en":"A valid inference whose model-specific postprocessor finds no detections.","zh-TW":"有效推論，模型特定後處理未找到物件。"},"output":{"en":"ok with an empty detection list; raw tensors still follow the model.","zh-TW":"ok 與空偵測清單；原始張量仍須符合模型。"},"acceptance":{"en":"Do not treat an all-zero tensor as universally equivalent to no detections.","zh-TW":"不可把全零張量一律視為沒有偵測。"}},{"scenario":{"en":"Tensor mismatch","zh-TW":"張量不相符"},"input":{"en":"Wrong dtype, shape or unsupported operation.","zh-TW":"型別、形狀錯誤或不支援的運算。"},"output":{"en":"error; no usable output; include a bounded diagnostic.","zh-TW":"error；沒有可用輸出；提供有限範圍診斷。"},"acceptance":{"en":"Reject the input rather than silently reshaping its meaning.","zh-TW":"拒絕輸入，不得靜默改變資料意義。"}},{"scenario":{"en":"Accelerator unavailable","zh-TW":"加速器不可用"},"input":{"en":"Requested GPU/NPU cannot execute the selected model.","zh-TW":"要求的 GPU／NPU 無法執行選定模型。"},"output":{"en":"Explicit failure or a configured CPU fallback with actual backend disclosed.","zh-TW":"明確失敗，或依設定改用 CPU 並揭露實際後端。"},"acceptance":{"en":"Do not claim GPU/NPU acceleration or measured latency without evidence.","zh-TW":"無證據不得宣稱 GPU／NPU 加速或實測延遲。"}}],"decisions":[[{"en":"Result states","zh-TW":"結果狀態"},{"en":"ok means the selected operation returned a valid result; a valid empty result differs from error. Pending work remains pending until a terminal result. Do not infer real-world correctness from API success.","zh-TW":"ok 表示所選操作回傳有效結構；有效空結果與 error 不同。未完成工作保持 pending 直到終態。API 成功不代表現實判斷必然正確。"}],[{"en":"Reproducibility","zh-TW":"可重現性"},{"en":"Record input ID, library/model version, configuration, runtime and coordinate/score conventions. Examples contain invented sample values.","zh-TW":"記錄輸入識別、函式庫／模型版本、設定、執行環境及座標／分數慣例。範例數值為示意。"}],[{"en":"Acceptance — proposed","zh-TW":"建議驗收"},{"en":"Use representative authorized samples plus empty, malformed and unavailable-runtime cases. Agree quality and latency targets before running tests. No measured accuracy, cost or speed is claimed.","zh-TW":"使用授權代表樣本，加上空結果、格式錯誤與環境不可用案例。測試前先約定品質與延遲目標；不宣稱已量測準確率、成本或速度。"}],[{"en":"Operation boundary","zh-TW":"操作範圍"},{"en":"Illustrative tensor inference contract. Tensor shape, dtype, normalization and labels must come from the actual model; no inference or benchmark was run.","zh-TW":"張量推論示意契約。張量形狀、型別、正規化與標籤須依實際模型定義；未執行推論或效能測試。"}]]},"schema_version":"1.0.0","type":"development-proposal","product_id":"industrial-api:LiteRT","name":"LiteRT","provider":"Google","url":"https://smart-tools.ai/product/LiteRT","localized_urls":{"en":"https://smart-tools.ai/product/LiteRT","zh-TW":"https://smart-tools.ai/zh-tw/product/LiteRT"},"category":"edge","capability_id":"cap:edge-ai","technology_hub":"https://smart-tools.ai/industrial-ai/edge-ai","interface_kind":"SDK","deployment":"local","official_documentation":"https://developers.google.com/edge/litert","sources":["https://developers.google.com/edge/litert","https://developers.google.com/edge/litert/overview","https://developers.google.com/edge/litert/android","https://developers.google.com/edge/litert/next/npu","https://developers.google.com/edge/litert/conversion/overview","https://developers.google.com/edge/litert/migration","https://developers.google.com/edge/litert/conversion/tensorflow/quantization/model_optimization","https://developers.google.com/edge/litert/cli/installation","https://developers.google.com/edge/litert/microcontrollers/overview","https://developers.google.com/edge/litert/next/cpp_sdk","https://github.com/google-ai-edge/LiteRT","https://ai.google.dev/edge/litert"],"source_review":{"level":"P1","status":"official-source-reviewed","checked_at":"2026-10-08"},"provider_summary":{"en":"Run machine-learning inference on supported devices.","zh-TW":"在支援的裝置上執行機器學習推論。"},"proposed_product":{"en":"Mobile inference benchmark","zh-TW":"手機端推論基準測試"},"feasibility":{"tier":"integration","rationale":{"en":"Validate runtime, schemas or hardware together before estimating a deployable product.","zh-TW":"估算可交付產品前，需共同驗證執行環境、資料結構或硬體。"},"basis":"development-judgment;not-traffic-ranked"},"proposed_inputs":{"en":"One pinned model, representative inputs, target runtime and workload.","zh-TW":"一個鎖定版本的模型、代表性輸入、目標環境與工作量。"},"proposed_deliverable":{"en":"Predictions or deployment evidence with model version, latency and resource measurements.","zh-TW":"附模型版本、延遲與資源量測的預測或部署證據。"},"acceptance_criterion":{"en":"Verify outputs against a known sample and measure latency, memory and failed calls on the chosen target.","zh-TW":"用已知樣本驗證輸出，並在選定環境量測延遲、記憶體與失敗呼叫。"},"dependencies":{"en":"Model rights, supported operators, memory budget and hardware or serving infrastructure.","zh-TW":"模型使用權、支援的算子、記憶體預算與硬體或服務環境。"},"integration_condition":null,"proposed_adapter_envelope":{"provider":"Google","operation":"chosen-documented-operation","source_url":"https://developers.google.com/edge/litert","captured_at":"ISO-8601 timestamp","status":"ok|pending|unknown|failed","data":"provider response mapped by the team","evidence":"source references","errors":"explicit error details"},"adapter_envelope_status":"proposed-internal-contract;not-a-provider-response","development_status":"concept-specification","integration_test":"not-run","pricing_status":"provider-terms-review-required","estimate_status":"requires-access-and-sample-validation","traffic_status":"not-measured-in-this-assessment","measurement_events":["product_view","product_to_docs","product_to_spec","bridge_to_industrial_ai"]}