Serverless LLM Hosting.
No GPU Management. Ever.
Featherless handles the entire inference infrastructure — you just make API calls. 40,000+ models, flat monthly pricing or pay-as-you-go.
inference.py
# Already using OpenAI? This is your entire migration.
from openai import OpenAI
from openai import OpenAI
client = OpenAI (
base_url="https://api.featherless.ai/v1", # ← change this one line
api_key="your-featherless-key"
)
base_url="https://api.featherless.ai/v1", # ← change this one line
api_key="your-featherless-key"
)
response = client.chat.completions.(
model="meta-llama/Llama-3.3-70B-Instruct",
messages=[{"role": "user", "content": "Hello"}]
)
# No GPU setup. No model downloads. No infra to manage.
model="meta-llama/Llama-3.3-70B-Instruct",
messages=[{"role": "user", "content": "Hello"}]
)
# No GPU setup. No model downloads. No infra to manage.
OpenAI-compatible
AMD & Airbus backed
Open-source models only
Drag
By the numbers
40,000+
Open-source models available
< 5 min
To your first API call
$25 / month
Flat rate or pay-as-you-go
∞
Tokens — no per-token billing
Drag
What self-hosted LLM inference actually costs
Self-hosted inference means GPU provisioning, 50–140GB model downloads, VRAM tuning, and scaling under load — weeks of engineering before you write a single line of product code. Featherless eliminates all of it. The infrastructure is built, the models are loaded, you just call the API.
How serverless inference works on Featherless
You request a model via API.
Request
Featherless handles model loading, GPU
assignment, and request routing.
GPU assigned — A100 · us-east-1
Model weights loaded
Request queued and routed
You get a response within seconds of the first call.
Scaling is automatic
no configuration required.
no configuration required.
You pay a flat monthly fee regardless of how many requests you make. Or you can pick pay-as-you-go pricing structure.
Monthly cost
from $25
Unlimited tokens or pay-as-you-go
Drag
Why teams switch to Featherless
Every provider makes trade-offs. Here is exactly where Featherless wins — and why teams managing GPU costs come to us.
vs RunPod / Lambda Labs
You are paying for GPUs you are not using.
Self-managed GPU hosting gives you flexibility — but you pay for idle GPU time, cold
starts, model-weight downloads, and the engineering hours to keep it running. Every
model swap is a project. Every traffic spike is a risk.
Featherless removes all of that. The infrastructure is already built and provisioned.
You call an API.
The win
Featherless eliminates idle GPU costs and ops overhead entirely. No engineers
babysitting infrastructure.
vs Hugging Face Inference Endpoints
Per-second billing compounds fast.
Hugging Face Inference Endpoints is a solid product — but billing by the second and by token means your costs are unpredictable. At moderate scale, your monthly invoice grows nonlinearly with usage.
Featherless charges a flat monthly rate. Run 1M tokens or 100M — the bill is the same. Budgeting is simple.
The win
Flat-rate beats per-second billing at any meaningful volume. One number, every month.
vs Together AI / Fireworks AI
Per-token pricing breaks your budget at scale.
Per-token providers look cheap at low volume — but as you scale past 1M tokens/day, costs accelerate. At ~10M tokens/day, Featherless consistently undercuts per-token pricing by 1.5–2x.
And unlike pay-as-you-go, you never get a surprise at month end. Your costs are decided on day one.
The win
At 10M tokens/day, Featherless is 1.5–2x cheaper. The gap widens as you scale.
Predictable pricing that scales with you
Chat
Built for interactive chat with unlimited tokens.*
$25/month
- Context size up to 32K
- 4 concurrent units
Subscribe
Billed monthly. Cancel anytime.
developer
Build production Al with the fastest usage-based inference.
$50 credits/month
- Context size up to 256K
- 1 agent environment included
- Fastest response times
- Unused credits roll over
- Billed per token
Subscribe
Billed monthly. Cancel anytime.
business
Dedicated GPUs and the team to run them.
Custom
- Dedicated H100, MI325, B200 & B300 GPUs
- Engineering team included
- Gets cheaper over time with fine-tuning
- Burst & failover to Public Cloud
Talk to an Engineer
Annual contracts. Volume pricing.
*Chat plan is for interactive, human-driven use by the purchaser. Not for reselling, app/API traffic, background automation, or benchmarking. Misuse may lead to cancellation without refund.
Get started in minutes.
No infrastructure to manage. No GPU provisioning. 40,000+ models.
