Hyperbolic

The hyperbolic provider supports Hyperbolic's API, which provides access to various LLM, image generation, audio generation, and vision-language models through an OpenAI-compatible API format. This makes it easy to integrate into existing applications that use the OpenAI SDK.

Setup

To use Hyperbolic, you need to set the HYPERBOLIC_API_KEY environment variable or specify the apiKey in the provider configuration.

Example of setting the environment variable:

export HYPERBOLIC_API_KEY=your_api_key_here

Provider Formats

Text Generation (LLM)

hyperbolic:<model_name>

Image Generation

hyperbolic:image:<model_name>

Audio Generation (TTS)

hyperbolic:audio:<model_name>

Available Models

Text Models (LLMs)

DeepSeek Models

hyperbolic:deepseek-ai/DeepSeek-R1 - Best open-source reasoning model
hyperbolic:deepseek-ai/DeepSeek-R1-Zero - Zero-shot variant of DeepSeek-R1
hyperbolic:deepseek-ai/DeepSeek-V3 - Latest DeepSeek model
hyperbolic:deepseek/DeepSeek-V2.5 - Previous generation model

Qwen Models

hyperbolic:qwen/Qwen3-235B-A22B - MoE model with strong reasoning ability
hyperbolic:qwen/QwQ-32B - Latest Qwen reasoning model
hyperbolic:qwen/QwQ-32B-Preview - Preview version of QwQ
hyperbolic:qwen/Qwen2.5-72B-Instruct - Latest Qwen LLM with coding and math
hyperbolic:qwen/Qwen2.5-Coder-32B - Best coder from Qwen Team

Meta Llama Models

hyperbolic:meta-llama/Llama-3.3-70B-Instruct - Performance comparable to Llama 3.1 405B
hyperbolic:meta-llama/Llama-3.2-3B - Latest small Llama model
hyperbolic:meta-llama/Llama-3.1-405B - Biggest and best open-source model
hyperbolic:meta-llama/Llama-3.1-405B-BASE - Base completion model (BF16)
hyperbolic:meta-llama/Llama-3.1-70B - Best LLM at its size
hyperbolic:meta-llama/Llama-3.1-8B - Smallest and fastest Llama 3.1
hyperbolic:meta-llama/Llama-3-70B - Highly efficient and powerful

Other Models

hyperbolic:hermes/Hermes-3-70B - Latest flagship Hermes model

Vision-Language Models (VLMs)

hyperbolic:qwen/Qwen2.5-VL-72B-Instruct - Latest and biggest vision model from Qwen
hyperbolic:qwen/Qwen2.5-VL-7B-Instruct - Smaller vision model from Qwen
hyperbolic:mistralai/Pixtral-12B - Vision model from MistralAI

Image Generation Models

hyperbolic:image:SDXL1.0-base - High-resolution master (recommended)
hyperbolic:image:SD1.5 - Reliable classic Stable Diffusion
hyperbolic:image:SD2 - Enhanced Stable Diffusion v2
hyperbolic:image:SSD - Segmind SD-1B for domain-specific tasks
hyperbolic:image:SDXL-turbo - Speedy high-resolution outputs
hyperbolic:image:SDXL-ControlNet - SDXL with ControlNet
hyperbolic:image:SD1.5-ControlNet - SD1.5 with ControlNet

Audio Generation Models

hyperbolic:audio:Melo-TTS - Natural narrator for high-quality speech

Configuration

Configure the provider in your promptfoo configuration file:

providers:
  - id: hyperbolic:deepseek-ai/DeepSeek-R1
    config:
      temperature: 0.1
      top_p: 0.9
      apiKey: ... # override the environment variable

Configuration Options

Text Generation Options

Parameter	Description
`apiKey`	Your Hyperbolic API key
`temperature`	Controls the randomness of the output (0.0 to 2.0)
`max_tokens`	The maximum number of tokens to generate
`top_p`	Controls nucleus sampling (0.0 to 1.0)
`top_k`	Controls the number of top tokens to consider (-1 to consider all tokens)
`min_p`	Minimum probability for a token to be considered (0.0 to 1.0)
`presence_penalty`	Penalty for new tokens (0.0 to 1.0)
`frequency_penalty`	Penalty for frequent tokens (0.0 to 1.0)
`repetition_penalty`	Prevents token repetition (default: 1.0)
`stop`	Array of strings that will stop generation when encountered
`seed`	Random seed for reproducible results

Image Generation Options

Parameter	Description
`height`	Height of the image (default: 1024)
`width`	Width of the image (default: 1024)
`backend`	Computational backend: 'auto', 'tvm', or 'torch'
`negative_prompt`	Text specifying what not to generate
`seed`	Random seed for reproducible results
`cfg_scale`	Guidance scale (higher = more relevant to prompt)
`steps`	Number of denoising steps
`style_preset`	Style guide for the image
`enable_refiner`	Enable SDXL refiner (SDXL only)
`controlnet_name`	ControlNet model name
`controlnet_image`	Reference image for ControlNet
`loras`	LoRA weights as object (e.g., `{"Pixel_Art": 0.7}`)

Audio Generation Options

Parameter	Description
`voice`	Voice selection for TTS
`speed`	Speech speed multiplier
`language`	Language for TTS

Example Usage

Text Generation Example

prompts:
  - file://prompts/coding_assistant.json
providers:
  - id: hyperbolic:qwen/Qwen2.5-Coder-32B
    config:
      temperature: 0.1
      max_tokens: 4096
      presence_penalty: 0.1
      seed: 42

tests:
  - vars:
      task: 'Write a Python function to find the longest common subsequence of two strings'
    assert:
      - type: contains
        value: 'def lcs'
      - type: contains
        value: 'dynamic programming'

Image Generation Example

prompts:
  - 'A futuristic city skyline at sunset with flying cars'
providers:
  - id: hyperbolic:image:SDXL1.0-base
    config:
      width: 1024
      height: 1024
      cfg_scale: 7.0
      steps: 30
      negative_prompt: 'blurry, low quality'

tests:
  - assert:
      - type: is-valid-image
      - type: image-width
        value: 1920

Audio Generation Example

prompts:
  - 'Welcome to Hyperbolic AI. We are excited to help you build amazing applications.'
providers:
  - id: hyperbolic:audio:Melo-TTS
    config:
      voice: 'alloy'
      speed: 1.0

tests:
  - assert:
      - type: is-valid-audio

Vision-Language Model Example

prompts:
  - role: user
    content:
      - type: text
        text: "What's in this image?"
      - type: image_url
        image_url:
          url: 'https://example.com/image.jpg'
providers:
  - id: hyperbolic:qwen/Qwen2.5-VL-72B-Instruct
    config:
      temperature: 0.1
      max_tokens: 1024

tests:
  - assert:
      - type: contains
        value: 'image shows'

Example prompt template (prompts/coding_assistant.json):

[
  {
    "role": "system",
    "content": "You are an expert programming assistant."
  },
  {
    "role": "user",
    "content": "{{task}}"
  }
]

Cost Information

Hyperbolic offers competitive pricing across all model types (rates as of January 2025):

Text Models

DeepSeek-R1: $2.00/M tokens
DeepSeek-V3: $0.25/M tokens
Qwen3-235B: $0.40/M tokens
Llama-3.1-405B: $4.00/M tokens (BF16)
Llama-3.1-70B: $0.40/M tokens
Llama-3.1-8B: $0.10/M tokens

Image Models

Flux.1-dev: $0.01 per 1024x1024 image with 25 steps (scales with size/steps)
SDXL models: Similar pricing formula
SD1.5/SD2: Lower cost options

Audio Models

Melo-TTS: $5.00 per 1M characters

Getting Started

Test your setup with working examples:

npx promptfoo@latest init --example hyperbolic

This includes tested configurations for text generation, image creation, audio synthesis, and vision tasks.

Notes

Model availability varies - Some models require Pro tier access ($5+ deposit)
Rate limits: Basic tier: 60 requests/minute (free), Pro tier: 600 requests/minute
Recommended models: Use meta-llama/Llama-3.3-70B-Instruct for text, SDXL1.0-base for images
All endpoints use OpenAI-compatible format for easy integration
VLM models support multimodal inputs (text + images)

Setup​

Provider Formats​

Text Generation (LLM)​

Image Generation​

Audio Generation (TTS)​

Available Models​

Text Models (LLMs)​

DeepSeek Models​

Qwen Models​

Meta Llama Models​

Other Models​

Vision-Language Models (VLMs)​

Image Generation Models​

Audio Generation Models​

Configuration​

Configuration Options​

Text Generation Options​

Image Generation Options​

Audio Generation Options​

Example Usage​

Text Generation Example​

Image Generation Example​

Audio Generation Example​

Vision-Language Model Example​

Cost Information​

Text Models​

Image Models​

Audio Models​

Getting Started​

Notes​