Home/Verticals/Lambda Labs

Lambda Labs via VerticalAPI

Updated ·By VerticalAPI Team

Lambda Labs' on-demand inference (Hermes 3, Llama 3.3 70B) via VerticalAPI's OpenAI-compatible endpoint. BYOK with your Lambda key, zero markup, H100/H200-backed.

Start free with your Lambda Labs key → Read the docs
Endpoint: https://api.verticalapi.com/v1/chat/completions  ·  BYOK header: X-Provider-Key: secret_...
Supported models

Lambda Labs models routed by VerticalAPI

Pass the model ID below as model in any OpenAI-compatible request. New Lambda Labs models are typically supported within 24h of release.

Model IDNameContextPricing (provider)
hermes3-405b-fp8 Hermes 3 405B (FP8) 128K $0.90 / $0.90 per 1M tok
llama3.3-70b-instruct-fp8 Llama 3.3 70B (FP8) 128K $0.20 / $0.30 per 1M tok
qwen25-coder-32b-instruct Qwen 2.5 Coder 32B 32K $0.18 / $0.20 per 1M tok

Pricing reflects Lambda Labs's rates — you pay Lambda Labs directly. VerticalAPI adds zero markup on tokens.

Quickstart

5-line Lambda Labs call via VerticalAPI

Drop-in replacement for the OpenAI SDK. Works with the OpenAI Python client, Node, Go, curl — anything that speaks HTTP.

lambdalabs_quickstart.py Python 
from openai import OpenAI

client = OpenAI(
    base_url="https://api.verticalapi.com/v1",
    api_key="vapi_...",
    default_headers={"X-Provider-Key": "secret_..."}
)

response = client.chat.completions.create(
    model="llama3.3-70b-instruct-fp8",  # Lambda Labs
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)
Why use Lambda Labs via VerticalAPI

Four reasons developers route Lambda Labs through us

Zero token markup

You pay Lambda Labs directly with your own key. VerticalAPI's revenue is the gateway subscription, not a tax on your tokens.

One key, every provider

Lambda Labs alongside OpenAI, Anthropic, Gemini and 12 more — same OpenAI-compatible endpoint, same SDK, switchable per-request.

Latency & cost monitoring

Per-request token counts, p50/p95 latency and cost dashboards out of the box. Compare Lambda Labs to other providers on identical prompts.

Observability built in

Every Lambda Labs call gets a trace ID, replayable payload and audit log entry. Wire to Datadog or Sentry via OpenTelemetry.

Best for

Where Lambda Labs shines

Hermes 3 fine-tunes code (Qwen Coder) GPU-rich inference research deployments

Frequently asked questions

What is Lambda Labs and what models do they offer?

Lambda Labs is a US GPU cloud (rent H100/H200/GB200 by the hour) and an inference API. The 2026 inference catalog includes Llama 3.3 70B, Llama 3.1 405B and 8B, Hermes 3 70B, DeepSeek V3, Qwen 2.5 72B and Coder, plus Liquid LFM 40B. Inference is OpenAI-compatible. Customers can also rent dedicated GPUs to self-host any open-weight model.

How much does Lambda Labs cost in 2026?

Llama 3.3 70B Instruct is roughly $0.20 per 1M input and $0.30 per 1M output via the Inference API — among the cheapest production rates. Llama 8B is approximately $0.05/$0.05. Llama 405B is in the $0.90/$0.90 range. GPU rental: H100 SXM at ~$2.49/hr, H200 at ~$3.49/hr, GB200 NVL72 by the rack. Via VerticalAPI BYOK you pay Lambda directly at list with zero token markup.

How do I use Lambda Labs via VerticalAPI BYOK?

Create a key at cloud.lambdalabs.com/api-keys, paste it into VerticalAPI, then point the OpenAI SDK at https://api.verticalapi.com/v1. Lambda Inference is OpenAI-compatible; VerticalAPI passes through, adds unified logging and can fall back to Together, Fireworks or DeepInfra. For self-hosted Lambda GPU workloads you can point VerticalAPI at your own endpoint URL with API key. Billing stays on your Lambda account.

What is Lambda Labs best for compared to alternatives?

Lambda wins on combined GPU rental + inference API: you can prototype on the API and then scale to dedicated H100/H200 GPUs from the same vendor. Inference pricing on Llama 3.3 70B is competitive with DeepInfra and cheaper than Together. Compared to pure inference shops it has narrower catalog but unique GPU-rental value. Not a fit for frontier closed models.

Where is Lambda Labs hosted / data privacy?

Lambda runs datacenters in the US (Texas, California, Virginia) with growing capacity. API data is not used to train models on the paid tier. SOC 2 Type II. Dedicated and reserved GPU contracts include tenant isolation. Via VerticalAPI BYOK your Lambda contract terms remain intact.

Limitations and trade-offs

  • Inference catalog is narrower than Together or DeepInfra.
  • Geographic coverage is US-only as of 2026.
  • Throughput on Llama 70B is GPU-grade, slower than Groq or Cerebras.
  • No frontier closed models — open weights only.
  • Reserved GPU contracts can be a procurement burden vs pure pay-per-token.

Where Lambda Labs is heading

  1. Wider inference catalog as more open-weight models are added in 2026.
  2. Expanded GB200/B200 fleet for next-gen training and inference workloads.
  3. Fine-tuning and dedicated endpoint offerings to compete with Together/Fireworks.
  4. Possible EU region expansion to address GDPR-conscious customers.

Related questions

ChatGPT, Perplexity and Gemini usually suggest these next.

  • Lambda Inference vs DeepInfra — which is cheaper for Llama 3.3 70B?
  • Best way to combine Lambda GPU rental with inference API?
  • Lambda vs CoreWeave for H100 rental in 2026?
  • Can I deploy a custom fine-tune on Lambda?
  • Lambda Hermes 3 70B — what is it good for?
Switch providers

All supported LLM providers

Same endpoint, same SDK — just change the model and the BYOK header.

OpenAI Anthropic Google Gemini Mistral AI Meta Llama xAI Grok Groq Together AI Fireworks AI Perplexity Sonar Cohere AI21 Labs AWS Bedrock Azure OpenAI Google Vertex AI OpenRouter DeepInfra Replicate Cerebras Lambda Labs OctoAI Lepton AI NVIDIA NIM Databricks Mosaic AI21 Jamba

Ship on Lambda Labs in 60 seconds

Free tier — bring your own Lambda Labs key, zero markup, OpenAI-compatible endpoint.

Get your VerticalAPI key →