> ## Documentation Index
> Fetch the complete documentation index at: https://docs.together.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Get model limits

> Get model limits for a specific fine-tuning model.



## OpenAPI

````yaml GET /fine-tunes/models/limits
openapi: 3.1.0
info:
  title: Together APIs
  description: The Together REST API. See https://docs.together.ai for more details.
  version: 2.0.0
  termsOfService: https://www.together.ai/terms-of-service
  contact:
    name: Together Support
    url: https://www.together.ai/contact
  license:
    name: MIT
    url: https://github.com/togethercomputer/openapi/blob/main/LICENSE
servers:
  - url: https://api.together.ai/v1
security:
  - bearerAuth: []
paths:
  /fine-tunes/models/limits:
    get:
      tags:
        - Fine-tuning
      summary: Get model limits
      description: Get model limits for a specific fine-tuning model.
      parameters:
        - in: query
          name: model_name
          schema:
            type: string
            description: The model name to get limits for.
          required: true
      responses:
        '200':
          description: Model limits.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuneModelLimits'
        '404':
          description: Model not found or not supported for fine-tuning.
          content:
            application/json:
              schema:
                type: object
                properties:
                  message:
                    type: string
                    description: Error message explaining the model is not available.
      x-codeSamples:
        - lang: Shell
          label: cURL
          source: >
            curl
            "https://api.together.ai/v1/fine-tunes/models/limits?model_name=meta-llama/Meta-Llama-3.1-8B-Instruct-Reference"
            \
                 -H "Authorization: Bearer $TOGETHER_API_KEY"
components:
  schemas:
    FineTuneModelLimits:
      type: object
      description: Model limits for fine-tuning.
      required:
        - model_name
        - lora_training
        - max_num_epochs
        - max_num_evals
        - max_num_checkpoints
        - max_learning_rate
        - min_learning_rate
        - supports_full_training
        - supports_vision
        - supports_tools
        - supports_reasoning
        - merge_output_lora
        - min_max_seq_length
        - max_seq_length_sft
        - max_seq_length_dpo
        - default_gradient_accumulation_steps
      properties:
        model_name:
          type: string
          description: The name of the model.
        full_training:
          type: object
          description: Limits for full training.
          required:
            - max_batch_size
            - max_batch_size_dpo
            - min_batch_size
          properties:
            max_batch_size:
              type: integer
              description: Maximum batch size for SFT full training.
            max_batch_size_dpo:
              type: integer
              description: Maximum batch size for DPO full training.
            min_batch_size:
              type: integer
              description: Minimum batch size for full training.
        lora_training:
          type: object
          description: Limits for LoRA training.
          required:
            - max_batch_size
            - max_batch_size_dpo
            - min_batch_size
            - max_rank
            - target_modules
          properties:
            max_batch_size:
              type: integer
              description: Maximum batch size for SFT LoRA training.
            max_batch_size_dpo:
              type: integer
              description: Maximum batch size for DPO LoRA training.
            min_batch_size:
              type: integer
              description: Minimum batch size for LoRA training.
            max_rank:
              type: integer
              description: Maximum LoRA rank.
            target_modules:
              type: array
              items:
                type: string
              description: Available target modules for LoRA.
        max_num_epochs:
          type: integer
          description: Maximum number of training epochs.
        max_num_evals:
          type: integer
          description: Maximum number of evaluations.
        max_learning_rate:
          type: number
          description: Maximum learning rate.
        min_learning_rate:
          type: number
          description: Minimum learning rate.
        supports_full_training:
          type: boolean
          description: >-
            Whether the model supports full (non-LoRA) fine-tuning. When false,
            only LoRA fine-tuning is available and the full_training limits are
            reported as zero.
        supports_vision:
          type: boolean
          description: Whether the model supports vision/multimodal inputs.
        supports_tools:
          type: boolean
          description: Whether the model supports tool/function calling.
        supports_reasoning:
          type: boolean
          description: Whether the model supports reasoning.
        merge_output_lora:
          type: boolean
          description: >-
            Whether a merged checkpoint (the base model with the trained LoRA
            adapter fused in) is produced for LoRA fine-tunes of this model, in
            addition to the standalone adapter.
        default_gradient_accumulation_steps:
          type: integer
          description: >-
            Default gradient accumulation steps used when a fine-tune request
            omits the value or sets it to 0.
        max_num_checkpoints:
          type: integer
          description: >-
            Maximum number of checkpoints that can be saved during a fine-tuning
            job.
        min_max_seq_length:
          type: integer
          description: Minimum value allowed for the max_seq_length hyperparameter.
        max_seq_length_sft:
          type: integer
          description: Maximum sequence length supported for SFT training.
        max_seq_length_dpo:
          type: integer
          description: Maximum sequence length supported for DPO training.
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      x-bearer-format: bearer
      x-default: default

````