> ## Documentation Index > Fetch the complete documentation index at: https://docs.aireserve.com/llms.txt > Use this file to discover all available pages before exploring further. # Deploy a model > Serves a model `serverless` (adapters, per token) or `dedicated` (per hour, the first hour is checked against the wallet). Poll until `ready`, then send `servingModel`. Requires compute `manage` access. ## OpenAPI ````yaml /api-reference/openapi.json post /v1/training/deployments openapi: 3.0.3 info: title: AI Reserve Gateway API description: >- The AI Reserve API surface — OpenAI-compatible chat completions, Anthropic-compatible messages, Bedrock Converse, images, video, files, text-to-speech, realtime voice sessions, provider-hidden GPU infrastructure, and fine-tuning — all behind one endpoint and one API key. version: 1.0.0 servers: - url: https://api.aireserve.com security: - bearerAuth: [] tags: - name: Customers description: >- Per-end-customer usage, cost, and billable amounts for organizations that tag requests with their own customers. - name: GPU Infrastructure description: >- Provision and manage provider-hidden GPU instances. The recommended Instances API accepts workload requirements and an hourly price ceiling; AI Reserve handles provider placement internally. Every mutation is asynchronous and returns an operation to poll. - name: Customer keys description: >- Mint, list, and revoke API keys pinned to your own end customers (and their organizations), so spend splits per customer without per-request tagging. - name: AWS CLI login description: >- Browser-authorization endpoints consumed by `aws login --profile …` (AWS CLI v2.32.0+). All three routes are unauthenticated — the caller has no credential until `/v1/token` succeeds. - name: Fine-tuning description: >- Fine-tune open models on your own data. Data lives in an S3 bucket inside your organization's AWS hub account; you name a base, LoRA or full, a price ceiling and how the result must be servable, and AI Reserve places the run on a backend internally. The result is a model in your bucket you can deploy or download. paths: /v1/training/deployments: post: tags: - Fine-tuning summary: Deploy a model description: >- Serves a model `serverless` (adapters, per token) or `dedicated` (per hour, the first hour is checked against the wallet). Poll until `ready`, then send `servingModel`. Requires compute `manage` access. operationId: createTrainingDeployment parameters: [] requestBody: required: true content: application/json: schema: type: object properties: modelId: type: string format: uuid pattern: >- ^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$ name: type: string minLength: 1 maxLength: 120 kind: type: string enum: - serverless - dedicated costAcknowledged: type: boolean enum: - true required: - modelId - name - kind - costAcknowledged additionalProperties: false responses: '202': description: Accepted. content: application/json: schema: type: object properties: id: type: string format: uuid pattern: >- ^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$ modelId: type: string format: uuid pattern: >- ^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$ name: type: string kind: type: string enum: - serverless - dedicated backend: type: string state: type: string enum: - pending - provisioning - ready - failed - deleting - deleted servingModel: nullable: true description: The model id to send once ready. type: string hourlyRateUsd: nullable: true type: string error: nullable: true type: string createdAt: type: string required: - id - modelId - name - kind - backend - state - servingModel - hourlyRateUsd - error - createdAt additionalProperties: false '400': description: Invalid request or schema violation. content: application/json: schema: $ref: '#/components/schemas/TrainingError' '401': description: Missing or invalid API key. content: application/json: schema: $ref: '#/components/schemas/TrainingError' '403': description: Key lacks the required compute access (`read` or `manage`). content: application/json: schema: $ref: '#/components/schemas/TrainingError' '404': description: Resource not found or owned by another organization. content: application/json: schema: $ref: '#/components/schemas/TrainingError' security: - bearerAuth: [] - apiKeyAuth: [] components: schemas: TrainingError: type: object properties: error: type: object properties: message: type: string type: type: string enum: - invalid_request_error param: type: string nullable: true enum: - null code: type: string details: type: object additionalProperties: {} required: - message - type - param - code additionalProperties: false required: - error additionalProperties: false securitySchemes: bearerAuth: type: http scheme: bearer description: >- Your AI Reserve API key (aireserve_api_…) from the API Keys page in the portal (https://portal.aireserve.com/keys). apiKeyAuth: type: apiKey in: header name: x-api-key description: The same API key sent as an `x-api-key` header. ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.