Memvid uses local models for semantic search (embeddings), reranking, visual search (CLIP), Logic‑Mesh entity extraction (NER), and local enrichment workflows. Models are cached under MEMVID_MODELS_DIR (default ~/.memvid/models).
Some models are installed explicitly via memvid models install, while embedding/reranker models are auto-downloaded on first use (unless offline).
Quick Start
# See what's available / installed (no downloads)
memvid models list
# Install optional CLIP + NER models
memvid models install --clip mobileclip-s2
memvid models install --ner distilbert-ner
# Install optional local LLM for enrichment (GGUF)
memvid models install phi-3.5-mini
Model Types
| Type | How it’s fetched | Used by |
|---|
| Embedding | Auto-download on first use | put --embedding, find --mode sem/auto, ask --mode sem/hybrid |
| Reranker | Auto-download on first use | Hybrid ask/find (disable with --no-rerank) |
| CLIP | memvid models install --clip … | put --clip, find --mode clip |
| NER | memvid models install --ner … | put --logic-mesh, follow … |
| LLM (Enrich) | memvid models install … | enrich, put --contextual --contextual-model local |
| Whisper | Auto-download on first use | put --transcribe |
Embedding Models (Text Vectors)
Select the default embedding model with the global -m/--embedding-model flag. It can appear before or after the subcommand:
memvid put knowledge.mv2 --input docs/ --embedding -m bge-small
memvid -m openai-small put knowledge.mv2 --input docs/ --embedding
Common choices
| Model | Dimensions | Notes |
|---|
bge-small | 384 | Default local model (fastembed) |
bge-base | 768 | Higher quality local model |
nomic | 768 | High accuracy local model |
gte-large | 1024 | Best local semantic depth |
openai-small | 1536 | OPENAI_API_KEY required |
openai-large | 3072 | OPENAI_API_KEY required |
openai | 3072 | Alias for openai-large |
openai-ada | 1536 | Legacy OpenAI model |
External embedding APIs
export OPENAI_API_KEY=sk-...
memvid put knowledge.mv2 --input docs/ --embedding -m openai-small
ask/find auto-detect the correct embedding runtime from the .mv2 when vectors are present. Use --query-embedding-model (or global -m) only when you need an explicit override.
Reranking (Hybrid Precision)
memvid ask may use a cross-encoder reranker (auto-downloaded on first use). Disable it in gated/offline environments:
memvid ask knowledge.mv2 --question "…" --no-rerank
CLIP Models (Visual Search)
Install a CLIP model:
memvid models install --clip mobileclip-s2
memvid models install --clip mobileclip-s2-fp16
memvid models install --clip siglip-base
memvid put photos.mv2 --input ./images --clip
memvid find photos.mv2 --query "sunset over ocean" --mode clip
NER Model (Logic‑Mesh)
Install NER:
memvid models install --ner distilbert-ner
memvid put graph.mv2 --input docs/ --logic-mesh
memvid follow graph.mv2 traverse --start "Microsoft" --hops 2
Enrichment LLM Models
These are local GGUF models used by enrichment workflows (not by memvid ask):
memvid models install phi-3.5-mini
memvid models install phi-3.5-mini-q8
For memvid ask, choose a synthesis model with --use-model (e.g. --use-model openai, --use-model gemini-2.0-flash, or --use-model "ollama:qwen2.5:1.5b"). See Local Models with Ollama.
List / Verify / Remove
# Filter model list
memvid models list --model-type embedding
memvid models list --model-type clip --json
# Verify installed enrichment LLM models (phi-3.5-*)
memvid models verify
memvid models verify phi-3.5-mini
# Remove an enrichment LLM model
memvid models remove phi-3.5-mini --yes
Offline Mode
Set MEMVID_OFFLINE=1 to prevent downloads. In offline mode:
memvid models install … fails (it can’t download).- Embedding/reranker auto-download is blocked; run a semantic command once while online to populate caches.
Environment Variables
| Variable | Purpose |
|---|
MEMVID_MODELS_DIR | Model cache directory (default ~/.memvid/models) |
MEMVID_OFFLINE | Skip downloads/network (1 to enable) |
MEMVID_CLIP_MODEL | Default local CLIP model (e.g. mobileclip-s2) |
OPENAI_API_KEY | OpenAI embeddings / CLIP / LLM providers |
GEMINI_API_KEY | Gemini providers |
ANTHROPIC_API_KEY | Claude providers |
COHERE_API_KEY | Cohere embeddings |
VOYAGE_API_KEY | Voyage embeddings |
