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Lambda Labs | Leverage Lambda Labs' GPU cloud infrastructure for high-performance model training, fine-tuning, and inference at scale |
This provider enables you to use Lambda Labs models through their Inference API.
Lambda Labs offers an OpenAI-compatible API for various large language models including Llama models, DeepSeek, Hermes, and more. You can use it as a drop-in replacement for applications currently using the OpenAI API.
Generate a Cloud API key from the Lambda Cloud dashboard. Then set the LAMBDA_API_KEY
environment variable or pass it via the apiKey
configuration field.
export LAMBDA_API_KEY=your_api_key_here
Or in your config:
providers:
- id: lambdalabs:chat:llama-4-maverick-17b-128e-instruct-fp8
config:
apiKey: your_api_key_here
The Lambda Labs provider supports the following formats:
lambdalabs:chat:<model name>
- Uses any model with the chat completion interfacelambdalabs:completion:<model name>
- Uses any model with the completion interfacelambdalabs:<model name>
- Defaults to the chat completion interfaceThe Lambda Labs Inference API officially supports these models:
deepseek-llama3.3-70b
- DeepSeek Llama 3.3 70B modeldeepseek-r1-671b
- DeepSeek R1 671B modelhermes3-405b
- Hermes 3 405B modelhermes3-70b
- Hermes 3 70B modelhermes3-8b
- Hermes 3 8B modellfm-40b
- Liquid Foundation Model 40Bllama-4-maverick-17b-128e-instruct-fp8
- Llama 4 Maverick 17B model with 128 expert MoEllama-4-scout-17b-16e-instruct
- Llama 4 Scout 17B model with 16 expert MoEllama3.1-405b-instruct-fp8
- Llama 3.1 405B Instruct modelllama3.1-70b-instruct-fp8
- Llama 3.1 70B Instruct modelllama3.1-8b-instruct
- Llama 3.1 8B Instruct modelllama3.1-nemotron-70b-instruct-fp8
- Llama 3.1 Nemotron 70B Instruct modelllama3.2-11b-vision-instruct
- Llama 3.2 11B Vision model (supports images)llama3.2-3b-instruct
- Llama 3.2 3B Instruct modelllama3.3-70b-instruct-fp8
- Llama 3.3 70B Instruct modelqwen25-coder-32b-instruct
- Qwen 2.5 Coder 32B Instruct modelTo get the current list of available models, use the /models
endpoint:
curl https://api.lambda.ai/v1/models -H "Authorization: Bearer your_api_key_here"
The provider accepts all standard OpenAI parameters:
temperature
- Controls randomness (0.0 to 1.0)max_tokens
- Maximum number of tokens to generatetop_p
- Nucleus sampling parameterstop
- Sequences where the API will stop generating further tokensfrequency_penalty
- Penalizes frequent tokenspresence_penalty
- Penalizes new tokens based on presence in text# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
description: Lambda Labs model evaluation
prompts:
- You are an expert in {{topic}}. Explain {{question}} in simple terms.
providers:
- id: lambdalabs:chat:llama-4-maverick-17b-128e-instruct-fp8
config:
temperature: 0.7
max_tokens: 1024
- id: lambdalabs:chat:llama3.3-70b-instruct-fp8
config:
temperature: 0.7
max_tokens: 1024
tests:
- vars:
topic: quantum computing
question: Explain quantum entanglement in simple terms
assert:
- type: contains-any
value: ['entangled', 'correlated', 'quantum state']
- vars:
topic: machine learning
question: What is the difference between supervised and unsupervised learning?
assert:
- type: contains
value: 'labeled data'
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