id: BAAI__bge-reranker-v2-m3__candidate
status: candidate
name: bge-reranker-v2-m3
org: BAAI
source:
  kind: huggingface
  url: https://huggingface.co/BAAI/bge-reranker-v2-m3
  revision: main
  model_card_url: https://huggingface.co/BAAI/bge-reranker-v2-m3
  project_url: https://github.com/FlagOpen/FlagEmbedding
license:
  spdx: Apache-2.0
  url: https://huggingface.co/BAAI/bge-reranker-v2-m3
  allows_offline_retention: true
  allows_local_ops: true
  allows_fine_tune: true
  notes: "Confirm SPDX on card."
profile:
  summary: "Cross-encoder reranker companion to BGE-M3 for higher-precision RAG."
  original_source: https://huggingface.co/BAAI/bge-reranker-v2-m3
  use_cases:
    - "Second-stage rerank of top-k chunks from BGE-M3 (or hybrid) retrieval"
    - "Improving answer grounding for NetKingdom / ops runbook Q&A"
    - "Eval A/B of retrieval quality without changing the generator"
    - "Low-cost precision boost on multilingual corpora"
  sweet_spots:
    - "Cheap RAG quality win after a solid bi-encoder"
    - "Small VRAM; easy always-on sidecar"
    - "Same BAAI/FlagEmbedding family as BGE-M3"
  not_ideal_for:
    - "First-stage retrieval over full corpora (too slow as sole retriever)"
    - "Generation / chat"
    - "When latency budget forbids a second pass"
  capability_notes: >
    Lightweight multilingual cross-encoder from the BGE family. W-tier optional
    after R spine; high value per byte when RAG is a primary workload.
swot:
  strengths:
    - "Material precision lift for little disk/VRAM"
    - "Proven pairing with BGE-M3"
    - "Apache-friendly open stack"
  weaknesses:
    - "Cross-encoder cost scales with candidate count"
    - "Not a substitute for better chunking or generators"
  opportunities:
    - "Default two-stage pipeline for lab RAG demos"
    - "Tune candidate depth (k) per latency tier"
  threats:
    - "Newer BGE / open rerankers may supersede this checkpoint"
    - "LLM-as-judge rerank experiments may reduce need for a dedicated model"
size:
  total_bytes: 0
  total_human: "~1–2 GB (estimate)"
hardware_class:
  min_vram_gb_q4: 1
  min_vram_gb_fp16: 2
  notes: "Companion to bge-m3"
axes: [B]
priority: medium
collection:
  approved_by: ""
  approved_at: null
  downloaded_at: null
  downloaded_by: ""
  storage_path: ""
  brief_refs:
    - research/2026-07-24-baseline-field-survey.md
reason: "P1/W — cheap RAG quality win as companion to BGE-M3."
tags: [tier-w, reranker, rag]
companions:
  - BAAI__bge-m3__candidate
notes: ""
history:
  - at: "2026-07-24"
    event: nominated
    by: baseline-survey
    detail: "P1 recommendation from initial deep research."
  - at: "2026-07-28"
    event: profile_swot_added
    by: grok
    detail: "schema 0.2 profile + SWOT."
  - at: "2026-07-28"
    event: decision_pass
    by: bernd
    detail: "W — optional after BGE-M3 verified"