> ## Documentation Index > Fetch the complete documentation index at: https://docs.mka1.com/llms.txt > Use this file to discover all available pages before exploring further. # List leaderboard runs for an eval suite > Returns each ranking group's most recent completed runs for a suite in one request, with the group assignments in `groups`. A group is (model, targeted task) for task_ids-restricted runs and (model) for unrestricted runs (task_id null). Build boards from `groups`, not from run.models/run.task_ids — a returned run may name models or tasks whose groups it did not rank in. `truncated: true` means a server ceiling trimmed the aggregate; whole runs are kept in (best rank, first model, first task, id) order, so every group's newest runs survive before any group's fallbacks and no group is dropped for being old. Resume a truncated board by passing `next_cursor` back as `cursor` and unioning the responses. See the evals docs for grouping rationale and cost characteristics. ## OpenAPI ````yaml https://apigw.mka1.com/speakeasy.json get /api/v1/llm/evals/suites/{suite_id}/leaderboard-runs openapi: 3.1.1 info: title: MKA1 API version: 1.1.0 description: >- The MKA1 API is a RESTful API that provides access to the MKA1 platform. Learn how to get started with the API and the TypeScript SDK [here](https://mka1.apidocumentation.com/guides/getting-started). license: name: Proprietary servers: - url: https://apigw.mka1.com description: MKA1 API Gateway - url: / description: Relative server URL (configurable via SDK constructor) security: [] tags: - name: Resource Authorization description: >- Manage permissions for LLM resources. Create resources, grant/revoke permissions, and delete resources. Only resource owners can grant, revoke, or delete permissions. x-displayName: Resource Authorization - name: Embeddings description: >- Text embedding API endpoints for generating vector representations of text. Create semantic embeddings for search, clustering, and similarity matching using various embedding models. x-displayName: Embeddings - name: Feedback description: >- User feedback API for rating and commenting on chat completions. Collect thumbs up/down ratings and detailed feedback to improve model responses and track user satisfaction. x-displayName: Feedback - name: Images description: >- Image generation API endpoints for creating images from text descriptions. Generate images with control over size, quality, and style. x-displayName: Images - name: MCP Vault description: >- MCP vault API for storing user-owned MCP server configurations and encrypted credentials. Agents reference vault IDs so secrets are resolved only at tool execution time. x-displayName: MCP Vault - name: Speech description: >- Speech API endpoints for audio processing. Convert text to natural-sounding speech (TTS) or transcribe speech to text (STT) in different languages. x-displayName: Speech - name: Usage description: >- Usage tracking and analytics API for monitoring token consumption, request counts, and cost analysis. View detailed statistics per user, model, and time period. x-displayName: Usage - name: Extract description: >- Structured data extraction API for extracting information from files. Define JSON schemas to extract structured data from images, PDFs, and documents. Supports reusable schema templates. x-displayName: Extract - name: Text Classification description: >- Text classification API for categorizing text into predefined labels. Use AI models to classify text content for sentiment analysis, topic categorization, and content moderation. x-displayName: Text Classification - name: Responses description: >- Agent-powered responses API for creating AI agents with autonomous tool usage. Build conversational assistants that can use web search, file operations, image generation, code execution, computer use simulation, and MCP integrations. Supports background processing, streaming, and real-time status tracking. x-displayName: Responses - name: Files description: >- File management API for uploading, storing, and managing files with automatic expiration and S3 integration. Upload files that can be used with Assistants, Vector Stores, and other features. Files are stored in S3 with metadata tracked in PostgreSQL. Supports automatic cleanup of expired files. x-displayName: Files - name: Vector Stores description: >- Vector store API for storing and searching documents using embeddings. Create vector stores, upload files with automatic chunking and embedding generation, and perform semantic search. Files are processed asynchronously using Temporal workflows for durability. Supports automatic cleanup of expired stores and LanceDB for efficient vector storage. x-displayName: Vector Stores - name: Conversations description: >- Conversation management API for storing and retrieving conversation state across Response API calls. Create conversations, add items (user messages, assistant messages, system messages), and maintain conversation history. Supports metadata tracking and multi-turn dialogue state management. x-displayName: Conversations - name: Guardrails description: >- AI safety guardrails API for configuring content moderation and security policies. Set up ban word lists, prompt injection detection, and system prompt leakage prevention. Guardrails apply to all requests from an account and can be tested before deployment. x-displayName: Guardrails - name: Models description: >- Model listing API for discovering available models. Returns model IDs, ownership, and metadata for all registered models in the gateway. x-displayName: Models - name: Skills description: >- Skills API for managing versioned bundles of instructions and files following the Agent Skills standard. Create, version, and download reusable skill packages that include SKILL.md manifests for agent environments. x-displayName: Skills - name: Chat Completions description: >- **Deprecated: Use the Responses API (`/api/v1/llm/responses`) instead.** Chat completion endpoints with support for streaming, tool calls, and multiple providers. x-deprecated: true x-displayName: Chat Completions - name: Batches x-displayName: Batches - name: Evals x-displayName: Evals - name: Fine-Tuning x-displayName: Fine-Tuning - name: Memory Stores x-displayName: Memory Stores - name: Prompts x-displayName: Prompts - name: API Key x-displayName: API Key - name: Organization x-displayName: Organization - name: Cluster Admin x-displayName: Cluster Admin - name: Sessions description: Create, inspect, access, and terminate sandbox sessions. x-displayName: Sessions - name: Browser description: >- Connect to browser sessions through the gateway port proxy. Browser sessions expose a Chrome DevTools Protocol endpoint on port 9222. x-displayName: Browser - name: Execution description: Run shell commands and code inside an existing sandbox session. x-displayName: Execution - name: Workspace description: >- Inspect the workspace manifest, transfer files or archives, and download generated artifacts. x-displayName: Workspace - name: Sandbox Usage description: >- Aggregate sandbox usage statistics across sessions, execution, and workspace operations. x-displayName: Sandbox Usage - name: Sandbox Pricing description: >- Cluster-admin management of the sandbox compute rate card used for budgeted spend. x-displayName: Sandbox Pricing - name: Agents description: Create and manage reusable agent definitions. x-displayName: Agents - name: Agent Versions description: Inspect an agent's configuration history and roll back to a prior version. x-displayName: Agent Versions - name: Agent Runs description: Execute saved agents and inspect persisted run results. x-displayName: Agent Runs - name: Agent Connectors description: >- Connect saved agents to external messaging channels such as Telegram, including text, photo, and supported document exchange. x-displayName: Agent Connectors - name: Agent Schedules description: Create and manage scheduled or recurring saved agent runs. x-displayName: Agent Schedules - name: schema-4_other x-displayName: other - name: Budgets x-displayName: Budgets - name: Settings x-displayName: Settings - name: Compute Jobs x-displayName: Compute Jobs - name: Compute Services x-displayName: Compute Services - name: Compute Catalog x-displayName: Compute Catalog - name: Compute Secrets x-displayName: Compute Secrets - name: Compute Usage x-displayName: Compute Usage - name: Compute Tenants x-displayName: Compute Tenants - description: Create, list, read, update, and delete repositories. name: Repositories x-displayName: Repositories - description: Manage a repository's explicit collaborators (readers/writers). name: Collaborators x-displayName: Collaborators paths: /api/v1/llm/evals/suites/{suite_id}/leaderboard-runs: get: tags: - Evals summary: List leaderboard runs for an eval suite description: >- Returns each ranking group's most recent completed runs for a suite in one request, with the group assignments in `groups`. A group is (model, targeted task) for task_ids-restricted runs and (model) for unrestricted runs (task_id null). Build boards from `groups`, not from run.models/run.task_ids — a returned run may name models or tasks whose groups it did not rank in. `truncated: true` means a server ceiling trimmed the aggregate; whole runs are kept in (best rank, first model, first task, id) order, so every group's newest runs survive before any group's fallbacks and no group is dropped for being old. Resume a truncated board by passing `next_cursor` back as `cursor` and unioning the responses. See the evals docs for grouping rationale and cost characteristics. operationId: listEvalSuiteLeaderboardRuns parameters: - name: suite_id in: path required: true schema: type: string example: eval_suite_aa87e2b1112a455b8deabed784372198 - name: suite_version in: query schema: type: integer minimum: 1 maximum: 2147483647 description: >- Narrow the ranking to runs recorded against one version of the suite. Scores are only comparable within a version, so leaderboard consumers should pass the version they score. A version the suite does not have returns an empty list, not 404, so it reads the same as a version with no completed runs yet. allowEmptyValue: true example: 1 - name: per_group in: query schema: type: integer minimum: 1 maximum: 20 default: 5 description: >- How many most-recent completed runs to keep per ranking group. A group is (model, targeted task) for task_ids-restricted runs — historical imports commit one run per model and task, so their boards assemble at per_group=1 — and (model) for unrestricted runs, which cover every task of their version. More than 1 lets a consumer fall back to an earlier run for a task whose newest run lacks usable stats. allowEmptyValue: true example: 5 - name: model in: query schema: type: string minLength: 1 maxLength: 255 description: >- Narrow the ranking to one model's groups. Useful when the consumer already knows its board axes; for discovering and paging past a truncated response, use cursor/next_cursor. An empty value is rejected rather than treated as omitted. allowEmptyValue: true example: meetkai:qwen3.5-35b-a3b - name: cursor in: query schema: type: string minLength: 1 maxLength: 2048 description: >- Opaque resume cursor from a previous truncated response's next_cursor. Continues the ranking exactly where the previous page stopped — inside a model or a rank tier when that is where the cut landed. Pass it back verbatim; a malformed value is a 400. Page with a fixed filter set, like the run-list cursor. allowEmptyValue: true - name: X-On-Behalf-Of in: header required: false schema: type: string description: Optional external end-user identifier forwarded by the API gateway. responses: '200': description: OK content: application/json: schema: type: object properties: object: const: eval.leaderboard_runs data: type: array items: type: object properties: id: type: string object: const: eval.run suite_id: type: string suite_version: type: integer minimum: -9007199254740991 maximum: 9007199254740991 suite_version_id: type: string status: $ref: '#/components/schemas/EvalRunStatus' models: type: array items: type: string task_ids: anyOf: - type: array items: type: string - type: 'null' judge_model: anyOf: - type: string - type: 'null' embedding_model: anyOf: - type: string - type: 'null' generation: type: object properties: instructions: type: string temperature: type: number minimum: 0 maximum: 2 top_p: type: number minimum: 0 maximum: 1 max_output_tokens: type: integer minimum: 1 maximum: 9007199254740991 max_gen_toks: type: integer minimum: 1 maximum: 9007199254740991 description: lm-eval alias for max_output_tokens. stop: anyOf: - type: string - type: array minItems: 1 items: type: string until: type: array minItems: 1 items: type: string description: lm-eval generate_until stop sequences. max_tool_calls: type: integer minimum: 1 maximum: 9007199254740991 reasoning: {} text: {} tools: type: array items: anyOf: - {} - type: 'null' tool_choice: {} parallel_tool_calls: type: boolean truncation: enum: - auto - disabled type: string service_tier: enum: - auto - default - flex - priority type: string presence_penalty: type: number minimum: -2 maximum: 2 frequency_penalty: type: number minimum: -2 maximum: 2 top_k: type: integer minimum: 0 maximum: 9007199254740991 min_p: type: number minimum: 0 maximum: 1 repetition_penalty: type: number minimum: 0 do_sample: type: boolean extra_body: type: object propertyNames: type: string additionalProperties: {} chat_template_kwargs: type: object propertyNames: type: string additionalProperties: {} prefill_think: anyOf: - type: boolean - type: string use_cache: type: boolean timeout_seconds: type: integer minimum: 1 maximum: 3600 max_retries: type: integer minimum: 0 maximum: 10 max_empty_retries: type: integer minimum: 0 maximum: 10 additionalProperties: {} request_counts: type: object properties: total: type: integer minimum: -9007199254740991 maximum: 9007199254740991 completed: type: integer minimum: -9007199254740991 maximum: 9007199254740991 failed: type: integer minimum: -9007199254740991 maximum: 9007199254740991 required: - total - completed - failed metrics: anyOf: - type: object propertyNames: type: string additionalProperties: {} - type: 'null' error: anyOf: - type: object propertyNames: type: string additionalProperties: {} - type: 'null' artifact_file_ids: type: array items: type: string metadata: type: object propertyNames: type: string maxLength: 64 additionalProperties: type: string maxLength: 512 created_at: type: integer minimum: -9007199254740991 maximum: 9007199254740991 started_at: anyOf: - type: integer minimum: -9007199254740991 maximum: 9007199254740991 - type: 'null' completed_at: anyOf: - type: integer minimum: -9007199254740991 maximum: 9007199254740991 - type: 'null' cancelled_at: anyOf: - type: integer minimum: -9007199254740991 maximum: 9007199254740991 - type: 'null' failed_at: anyOf: - type: integer minimum: -9007199254740991 maximum: 9007199254740991 - type: 'null' required: - id - object - suite_id - suite_version - suite_version_id - status - models - task_ids - judge_model - embedding_model - generation - request_counts - metrics - error - artifact_file_ids - metadata - created_at - started_at - completed_at - cancelled_at - failed_at description: The deduplicated runs behind `groups`, newest first. groups: type: array items: $ref: '#/components/schemas/EvalLeaderboardRunGroup' description: >- The server's group assignments — build boards from these, not from run.models/run.task_ids. Ordered by model, then task id with the covers-everything group first within each model, then rank; that ordering is contract. truncated: type: boolean description: >- True when a server ceiling trimmed the aggregate. Whole runs are kept in (rank, model, task) order — never dropped for being old; resume with `cursor: next_cursor`. next_cursor: anyOf: - type: string - type: 'null' description: >- Set when truncated: pass as `cursor` on the next request and union the responses until truncated is false to assemble the complete aggregate. Null when this response is complete. required: - object - data - groups - truncated - next_cursor example: object: eval.leaderboard_runs data: - id: eval_run_aa87e2b1112a455b8deabed784372198 object: eval.run suite_id: eval_suite_aa87e2b1112a455b8deabed784372198 suite_version: 1 suite_version_id: eval_sver_aa87e2b1112a455b8deabed784372198 status: in_progress models: - auto task_ids: null judge_model: auto embedding_model: auto generation: temperature: 0 max_output_tokens: 512 request_counts: total: 100 completed: 10 failed: 0 metrics: null error: null artifact_file_ids: [] metadata: purpose: mvp created_at: 1704067200 started_at: 1704067210 completed_at: null cancelled_at: null failed_at: null groups: - model: meetkai:qwen3.5-35b-a3b task_id: null rank: 1 run_id: eval_run_aa87e2b1112a455b8deabed784372198 truncated: false next_cursor: null security: - bearerAuth: [] x-codeSamples: - lang: python label: Python (SDK) source: |- from meetkai_mka1 import SDK with SDK( bearer_auth="", ) as sdk: res = sdk.llm.evals.list_suite_leaderboard_runs(suite_id="eval_suite_aa87e2b1112a455b8deabed784372198", suite_version=1, per_group=5, model="meetkai:qwen3.5-35b-a3b") # Handle response print(res) - lang: typescript label: Typescript (SDK) source: |- import { SDK } from "@meetkai/mka1"; const sdk = new SDK({ bearerAuth: "", }); async function run() { const result = await sdk.llm.evals.listSuiteLeaderboardRuns({ suiteId: "eval_suite_aa87e2b1112a455b8deabed784372198", suiteVersion: 1, model: "meetkai:qwen3.5-35b-a3b", }); console.log(result); } run(); - lang: csharp label: CSharp (SDK) source: >- using MeetKai.MKA1; using MeetKai.MKA1.Types.Components; using MeetKai.MKA1.Types.Requests; var sdk = new SDK(bearerAuth: ""); ListEvalSuiteLeaderboardRunsRequest req = new ListEvalSuiteLeaderboardRunsRequest() { SuiteId = "eval_suite_aa87e2b1112a455b8deabed784372198", SuiteVersion = 1, Model = "meetkai:qwen3.5-35b-a3b", }; var res = await sdk.Llm.Evals.ListSuiteLeaderboardRunsAsync(req); // handle response components: schemas: EvalRunStatus: enum: - queued - in_progress - finalizing - completed - failed - cancelling - cancelled type: string EvalLeaderboardRunGroup: type: object properties: model: type: string description: The group's model. task_id: anyOf: - type: string - type: 'null' description: >- The group's targeted task, or null for the per-model covers-everything group that unrestricted runs (no task_ids) rank in — those runs cover every task of their version. rank: type: integer minimum: -9007199254740991 maximum: 9007199254740991 description: >- 1 is the group's newest completed run. Ranks order runs within a group but are not slot indexes: under truncation a group's surviving ranks may be non-contiguous. run_id: type: string description: The run holding this rank; the full run object is in `data`. required: - model - task_id - rank - run_id securitySchemes: bearerAuth: type: http scheme: bearer bearerFormat: API Key description: >- Gateway auth: send `Authorization: Bearer `. For multi-user server-side integrations, you can also send `X-On-Behalf-Of: `. ````