Meta Llama 3.1 8B Instruct — Local Baseline Worker
Status: optional software contract implemented; no new Llama 3.1 inference has been executed by FrontierLab.
Why it joins
meta-llama/Llama-3.1-8B-Instruct fills the middle of FrontierLab's model-size spectrum.
Meta released Llama 3.1 on July 23, 2024. The 8B Instruct model is text-only, supports a 128K-token context, eight officially supported languages, Grouped-Query Attention, multilingual dialogue and tool-use-oriented workflows.
Official references:
FrontierLab does not add it because it is newer or stronger than Muse Glimmer. It joins as a mature, widely deployed medium-size baseline.
Role
The intended role is:
Local General-Purpose Baseline / Worker
It can run the same structured json(role, task, payload) interface used by FrontierLab research agents, but every receipt is permanently marked:
baseline_only = true
scientific_output_independently_verified = false
This makes it suitable for controlled A/B comparisons while keeping the verified Glimmer path distinct.
Future scale-vs-reliability comparison
A useful controlled comparison is:
Muse2-230M -> edge structured preprocessing
Llama 3.1 8B -> local general-purpose baseline
Muse Glimmer 30B -> verified scientific reasoning backend
Muse Spark 816B -> frontier multimodal reasoning
Run the same bounded structured task and compare:
- JSON validity;
- abstention rate;
- citation-ID validity;
- exact quotation validity;
- researcher intervention rate;
- latency;
- input/output size or token usage.
The goal is not to prove that larger models are always better. It is to identify the smallest model that can reliably perform each bounded job.
Runtime boundary
The default FrontierLab installation remains unchanged. No 8B checkpoint, Transformers runtime or GPU dependency is added to requirements.txt.
Llama31BaselineClient accepts an injected local runtime exposing:
runtime.complete(
messages=[...],
max_new_tokens=1024,
temperature=0.2,
top_p=0.9,
)
This allows llama.cpp, Transformers or another local serving layer to be wrapped without coupling FrontierLab to one runtime.
Scientific boundary
Llama 3.1 8B can participate in a controlled baseline version of evidence extraction, skeptical review or hypothesis formatting, but its output still goes through the same:
source ID -> exact quote -> human review -> evaluation -> planning gate
It never receives authority to approve its own scientific output.
Run the zero-network preflight:
python -m scripts.llama31_baseline_preflight
No checkpoint is downloaded by that command.