ai.openmark由 openmark.ai 发布官方发布者v1.0.0更新于 Oct 25, 2026
通过真实API调用在100多个LLM上测试你的提示词，选出能通过的最便宜模型。
AI 翻译由 AI 模型根据下方的原文描述翻译，可能有误。
Benchmark your own prompt on 100+ LLMs with real API calls; pick the cheapest model that passes.
OpenMark 的托管 MCP 服务（openmark.ai），由 openmark.ai 发布；需要 API 密钥；Streamable HTTP；9 个工具。
暂无 AI 概览：以下信息来自注册中心条目和服务本身。
Web executable，通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体，或 SourceWeft 对话中。智能体会读取该服务器的安装指南，先向你展示发布者、端点和登录方式，经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/ai.openmark%2Fopenmark/install.md，并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前，先告诉我它的发布者、端点和登录方式，等我确认。不要把 API 密钥写进命令或我会提交的文件；问我密钥应从哪里获取。把它添加到你客户端的 mcpServers 配置中。
{
"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.
无需输入参数。
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必填已满足适用检查项的 83%
该评分衡量此收录条目的完整程度，依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价，也不表示服务器安全或当前可用：可连通性是带日期的检查结果，评分也不包含安装量或用户评价。
请声明包含 README 的 GitHub 仓库，或在 OAuth 受保护资源元数据中提供 resource_documentation。
托管服务按其提供方的条款使用，因此这里不要求许可证。此检查项不计入百分比。