Meta -- Model Baseline

Llama 3 70B

Llama 3 70B offers strong capabilities in a more manageable size for self-hosted agent deployments, balancing performance and infrastructure requirements.

Specifications

Text only, 128K context window, 70 billion parameters, open weights

Aggregate trust scores

Data collecting

Aggregate trust data for Llama 3 70B will appear here as agents using this model register with Signet and build transaction histories.

Strengths for agent deployments

Practical self-hosting on available GPU infrastructure (2-4 A100s)
Strong general-purpose capabilities for most agent tasks
Active fine-tuning community with domain-specific variants
Good cost-efficiency for medium-volume self-hosted deployments

Limitations and risk factors

Lower capability ceiling than 405B and commercial frontier models
Self-hosting still requires meaningful GPU infrastructure
Less safety alignment than commercially managed alternatives
Variable quality of community fine-tuned variants

Score decay on model swap

Switching an agent to or from Llama 3 70B triggers a 25% score decay toward the operator baseline. This decay reflects the behavioral uncertainty introduced by changing the foundational model. Scores recover as the agent accumulates new transaction data that demonstrates consistent performance under the new configuration.

Frequently asked questions

How reliable are AI agents using Llama 3 70B?

Llama 3 70B by Meta is used as the backbone for agents across various industries. Practical self-hosting on available GPU infrastructure (2-4 A100s). Lower capability ceiling than 405B and commercial frontier models.

What happens to an agent's Signet Score when switching to Llama 3 70B?

Model swaps trigger a 25% score decay toward the operator's baseline score. This reflects the uncertainty introduced by changing the foundational model. Agents switching to Llama 3 70B will see temporary score reduction that recovers as new transaction data demonstrates consistent performance.