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Meta: Llama 3.1 70B Instruct

meta-llama/llama-3.1-70b-instruct

↓ runs free on your own hardware⚙ tool calling

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...

specs & pricing
Type
text
Provider
meta-llama
Model ID
meta-llama/llama-3.1-70b-instruct
Capabilities
tools
Context window
131K tokens
Self-hostable
Yes — runs on your own GPU
Input price
$0.44 / 1M tokens
Output price
$0.44 / 1M tokens

Cloud price is billed from prepaid credits when a request fails over to the cloud. Open-weight models run free on GPUs you own — the gateway routes to your nodes first.

What it costs to run

cloud · 1M in + 1M out

$0.88

$0.44 for a million input tokens plus $0.44 for a million output tokens, billed from credits only when a request fails over to the cloud.

your hardware

$0 / token

Served from a workstation or on-prem server you own, there is no per-token fee — the marginal cost is power.

Run it on your own hardware

Estimated GPU memory for Meta: Llama 3.1 70B Instruct (70B parameters), for the weights alone — add room for the context cache.

Q4_K_M
~40.5 GBfits a 48 GB card
Q8_0
~69.9 GBfits a 80 GB card
FP16 / BF16
~131.1 GBmulti-GPU or large unified memory

Install the agent on the machine and it dials out to the gateway over a single WebSocket — no port forwarding or inbound firewall rules. Requests for this model go to your node first and fail over to the cloud only when it can't serve.

/// initialize

Call Meta: Llama 3.1 70B Instruct through one OpenAI-compatible endpoint.

Serve it from hardware you own, with cloud failover when your nodes are busy or offline.

no credit card · 2 nodes free · openai-compatible

Frequently asked questions

What is the context window of Meta: Llama 3.1 70B Instruct?
Meta: Llama 3.1 70B Instruct accepts up to 131,072 tokens (131K) of context per request.
How much does Meta: Llama 3.1 70B Instruct cost per million tokens?
Through Wide Area Intelligence, Meta: Llama 3.1 70B Instruct costs $0.44 per 1M input tokens and $0.44 per 1M output tokens when served from the cloud, billed from prepaid credits. A workload of 1M input plus 1M output tokens costs $0.88.
Can I run Meta: Llama 3.1 70B Instruct on my own hardware?
Yes — Meta: Llama 3.1 70B Instruct is an open-weight model you can run on a workstation or on-prem server you own. At Q4_K_M it needs roughly 40.5 GB of GPU memory, plus room for the context cache — it fits a single 48 GB card. Wide Area Intelligence routes requests to your own nodes first and fails over to the cloud only when they can't serve.

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