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

This calls Hyperbolic's fixed Melo TTS endpoint. The local provider identity defaults to hyperbolic:audio:Melo-TTS. An optional suffix is retained for compatibility and does not select a different remote model.

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 text-to-speech endpoint

Hyperbolic has announced an upcoming Melo TTS sunset without a removal date. The existing hyperbolic:audio:Melo-TTS route remains compatible.

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
cost, inputCost, outputCost	Override promptfoo's pricing estimates. Use inputCost and outputCost for asymmetric pricing; cost remains the shared fallback.
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
language	Language code (default: EN)
speaker	Language-specific speaker, such as EN-US, EN-BR, EN-INDIA, EN-AU
speed	Speech speed multiplier (0.1–5, default: 1)
sdp_ratio	Prosody variation (0–1)
noise_scale	Speech variation (0–1)
noise_scale_w	Timing variation (0–1)

The prompt supplies the required text field. Prompt-level configuration overrides these provider options. The native audio API returns base64-encoded MP3 audio and does not document model or voice parameters. The provider omits config.model and config.voice for the native endpoint and forwards them only to custom endpoints. Use speaker for native voice selection; changing the route suffix never adds a model field.

For a custom audio endpoint, set apiBaseUrl to its base URL, including any version prefix and omitting the trailing slash. The provider appends /audio/generation. Custom endpoints retain the legacy WAV output metadata and $0.001 per 1,000-character estimate; these defaults do not establish the custom service's format or pricing.

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
    config:
      language: 'EN'
      speaker: 'EN-US'
      speed: 1.0

tests:
  - assert:
      - type: javascript
        value: "typeof output === 'string' && output.length > 0"

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: promptfoo estimates $5.00 per 1M characters for Hyperbolic's native endpoint, following its audio pricing documentation.

Getting Started

Test your setup with working examples:

npx promptfoo@latest init --example provider-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)