ai.openmark由 openmark.ai 發布官方發布者v1.0.0更新於 Oct 25, 2026
通過真實API呼叫在100多個LLM上測試你的提示詞，選出能通過的最便宜模型。
AI 翻譯由 AI 模型根據下方的原文描述翻譯，可能有誤。
Benchmark your own prompt on 100+ LLMs with real API calls; pick the cheapest model that passes.
OpenMark 的託管 MCP 服務（openmark.ai），由 openmark.ai 發布；需要 API 金鑰；Streamable HTTP；9 個工具。
暫無 AI 概覽：以下資訊來自註冊中心條目和服務本身。
Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/ai.openmark%2Fopenmark/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"openmark": {
"type": "http",
"url": "https://openmark.ai/mcp",
"headers": {
"Authorization": "Bearer <YOUR_TOKEN>"
}
}
}
}Task YAML format
How to write an OpenMark task: the YAML structure, all 18 scoring modes, and tips. Call this before writing a task. Pass a topic for the full detail on one subject (the app's Task Guide): fields, scoring, composite, chaining, documents, examples, best_practices, or a scoring mode name.
topicCheck a task
Check a task YAML the way OpenMark will before running it: structure, scoring settings, and the test limit of the user's plan. Free, saves nothing. Returns the problems to fix and warnings worth a look.
task_yaml必填List models
Current OpenMark model ids with list prices ($ per 1M tokens), as text and as a structured list. Use these ids in run_benchmark. Append @low, @medium or @high to a reasoning model id to set its reasoning effort.
searchimages_onlymax_output_pricePrepare file attachments
Get an upload_uid and a one-hour upload link (no API key needed) for images, PDFs or text documents, with the exact curl command. Upload the files, reference them by file name in each test's attachments list, then pass the upload_uid to estimate_cost / run_benchmark.
file_namesEstimate a run's cost
Credits a run_benchmark call would use, before spending anything: the expected total, the split per model, the balance needed to start, the worst case, and the user's balance. Same inputs and run settings as run_benchmark. Use it to drop an expensive model, or to compare settings (e.g. max_tokens), before running.
models必填presetfail_fasttask_yaml必填max_tokensupload_uidcustom_timeoutstability_runstemp_preferencetimeout_profiletemperature_discoveryRun a benchmark
Save a task (YAML, see get_task_format) to the user's OpenMark account and run it on the given models with real API calls. Returns a job_id and the expected cost; poll get_results. Spends the user's credits; pass max_credits to only start within a budget. Optional run settings match the app's Configure & Run panel (preset, stability_runs, max_tokens, temperature_discovery, temp_preference, timeout_profile, custom_timeout, fail_fast).
models必填presetfail_fasttask_yaml必填max_tokensupload_uidmax_creditscustom_timeoutstability_runstemp_preferencetimeout_profiletemperature_discoveryGet benchmark results
Status of a benchmark job, and once completed the ranked results (score, stability, cost per run, latency), the tests each model missed with its answer, a recommendation for the chosen objective and quick picks for the others.
job_id必填toleranceshow_missesoptimize_forAccount, credits and plans
The user's plan, credit balance and limits, and what a credit pack, Pro or Expert would unlock. Use it before large runs, or when a run is refused for credits or limits.
無需輸入參數。
Watch a task for better models
Watch the task of a completed job: when new or cheaper models ship, OpenMark re-tests up to 4 of them next to the user's pick and emails the user only when one beats it. Each check uses the user's credits at the normal rate.
modeljob_id必填已滿足適用檢查項的 83%
該評分衡量此收錄條目的完整程度，依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價，也不表示伺服器安全或目前可用：可連通性是帶日期的檢查結果，評分也不包含安裝量或使用者評價。
請宣告包含 README 的 GitHub 儲存庫，或在 OAuth 受保護資源後設資料中提供 resource_documentation。
託管服務按其提供方的條款使用，因此這裡不要求授權條款。此檢查項不計入百分比。