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 modelhyperbolic:deepseek-ai/DeepSeek-R1-Zero
- Zero-shot variant of DeepSeek-R1hyperbolic:deepseek-ai/DeepSeek-V3
- Latest DeepSeek modelhyperbolic:deepseek/DeepSeek-V2.5
- Previous generation model
Qwen Models
hyperbolic:qwen/Qwen3-235B-A22B
- MoE model with strong reasoning abilityhyperbolic:qwen/QwQ-32B
- Latest Qwen reasoning modelhyperbolic:qwen/QwQ-32B-Preview
- Preview version of QwQhyperbolic:qwen/Qwen2.5-72B-Instruct
- Latest Qwen LLM with coding and mathhyperbolic: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 405Bhyperbolic:meta-llama/Llama-3.2-3B
- Latest small Llama modelhyperbolic:meta-llama/Llama-3.1-405B
- Biggest and best open-source modelhyperbolic:meta-llama/Llama-3.1-405B-BASE
- Base completion model (BF16)hyperbolic:meta-llama/Llama-3.1-70B
- Best LLM at its sizehyperbolic:meta-llama/Llama-3.1-8B
- Smallest and fastest Llama 3.1hyperbolic: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 Qwenhyperbolic:qwen/Qwen2.5-VL-7B-Instruct
- Smaller vision model from Qwenhyperbolic: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 Diffusionhyperbolic:image:SD2
- Enhanced Stable Diffusion v2hyperbolic:image:SSD
- Segmind SD-1B for domain-specific taskshyperbolic:image:SDXL-turbo
- Speedy high-resolution outputshyperbolic:image:SDXL-ControlNet
- SDXL with ControlNethyperbolic: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)