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Rent Llama 3.1 8B in a private loop

Reliable conversational model
By Metallama3.1:8b8B parameters32K tokens of contextLlama 3.1 Community License

The most road-tested open model: half the tutorials, LoRA adapters and wrappers on the internet target it. Holds a long dialogue and barely needs prompt tuning — pick it when predictability and ecosystem matter.

GPU configurations for Llama 3.1 8B

1x V100

Best value
~28 tok/sup to 2 streams
$0.21per hour

1x RTX4090

~82 tok/sup to 4 streams
$0.55per hour

1x RTX5090

~108 tok/sup to 6 streams
$0.65per hour

1x A100

~72 tok/sup to 8 streams
$1.49per hour

1x H100

~118 tok/sup to 16 streams
$3.43per hour
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Billing follows server uptime by the hour.

Llama 3.1 8B benchmarks

as published by the model vendor
Llama 3.1 8B scores in public benchmarks
MMLU69.4
GSM8K84.5
HumanEval72.6

Other models in the private loop

FAQ

Frequently asked about renting Llama 3.1 8B

Which GPU does Llama 3.1 8B need?

The entry configuration is 1x V100, which delivers around 28 tokens per second. For more parallel requests and headroom on speed, go with 1x H100.

How much does Llama 3.1 8B cost?

An hour of Llama 3.1 8B runs from $0.21 to $3.43 depending on the GPU configuration. Billing is hourly: you pay for server time, not for tokens.

How do I call Llama 3.1 8B from my code?

Once deployed you get an OpenAI-compatible endpoint: point any OpenAI client at the base_url you receive and pass llama3.1:8b as the model name. Code written against the OpenAI API needs no changes.

Does the data stay private?

Yes. Llama 3.1 8B runs on a dedicated GPU server inside a private loop: requests and responses never reach the model vendor and are not used for training.

What context window and license does Llama 3.1 8B have?

Llama 3.1 8B holds 32K tokens of context per request and ships under the Llama 3.1 Community License license, so you can use it commercially on your own hosting terms.