freedom-intelligence/inventory/catalog/meta-llama__Llama-3.2-3B-Instruct__candidate.yaml
tegwick 77d4ffe86e Finish FI-WP-0002 and FI-WP-0003: daily rhythm and R-spine reserve.
Enable fi-daily-research-brief, prove fi_brief_status idempotence with the
2026-07-28 brief, approve R/S catalog entries, collect and verify embeds plus
Qwen3-8B and R1-Distill-14B on VAULT, and document residuals (HF-gated Llama,
deferred S giants, railiance ConfigMap apply).
2026-07-28 01:30:55 +02:00

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id: meta-llama__Llama-3.2-3B-Instruct__candidate
status: approved
name: Llama-3.2-3B-Instruct
org: meta-llama
source:
kind: huggingface
url: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
revision: main
model_card_url: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
project_url: https://www.llama.com/
license:
spdx: custom
url: https://ai.meta.com/llama/license/
allows_offline_retention: true
allows_local_ops: true
allows_fine_tune: true
notes: "Llama Community License — not MIT; review terms before commercial redistribution."
profile:
summary: "Tiny edge instruct for always-on and low-VRAM agent micro-services."
original_source: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
use_cases:
- "Always-on local helper with minimal power/VRAM"
- "Fast classification, routing, and short-form rewrites"
- "CPU or 48 GB GPU edge boxes"
- "Smoke-test harnesses before promoting to 8B+"
- "Embedded tooling demos and offline kiosks"
sweet_spots:
- "Latency and footprint over peak intelligence"
- "Huge Llama ecosystem (llama.cpp, Ollama, many templates)"
- "Cheap parallel micro-agents in a fleet"
not_ideal_for:
- "Serious coding or long documents"
- "Domain FT when quality matters (prefer 8B base)"
- "Standalone reasoning-heavy ops decisions"
capability_notes: >
Compact Meta instruct model. Best as a floor for local intelligence and
high-volume simple tasks, not as the lab's primary brain.
swot:
strengths:
- "Very small; runs almost anywhere in the lab"
- "Massive tooling and community template coverage"
- "Good enough for structured short outputs"
weaknesses:
- "Shallow capability; fails hard tasks silently if not constrained"
- "Custom Llama license (not pure OSS-permissive)"
- "HF gated access friction"
opportunities:
- "Fleet of specialized tiny adapters per workflow"
- "Guardrail / router model in front of larger backends"
threats:
- "Qwen/Gemma/Smol peers may outclass at same size"
- "License or regional policy changes for Llama family"
size:
total_bytes: 0
total_human: "~6 GB fp16 / ~2 GB Q4 (estimate)"
hardware_class:
min_vram_gb_q4: 3
min_vram_gb_fp16: 8
notes: "T0T1 edge / always-on"
axes: [B]
priority: high
collection:
approved_by: "bernd"
approved_at: "2026-07-28"
downloaded_at: null
downloaded_by: ""
storage_path: ""
brief_refs:
- research/2026-07-24-baseline-field-survey.md
reason: "P0/R edge instruct — tiny, huge ecosystem, good CPU/GPU floor for agents."
tags: [tier-r, instruct, edge, llama]
companions: []
notes: "HF gated model — need accepted license on account before download."
history:
- at: "2026-07-24"
event: nominated
by: baseline-survey
detail: "P0 recommendation from initial deep research."
- at: "2026-07-24"
event: profile_swot_added
by: grok
detail: "schema 0.2 profile + SWOT."
- at: "2026-07-28"
event: approved
by: bernd
detail: "R edge (HF gated — pull when token available)"