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Mahdi Bazrafshan 6c9cebaaa0 docs(research): add farsi embedding model research knowledge base

Body:
        Why:
        - Insurance RAG pipeline needs Farsi-optimized embeddings
        - Current local baseline (Nomic Embed) is English-only

        Changes:
        - 8 cloud model profiles with curl + python test commands
        - 5 local model profiles with VRAM, serving platform notes
        - Persian benchmark landscape (MIRACL-Fa, mMARCO, FaMTE, MTEB)
        - Decision report with ranked options and recommendations
        - Full comparison table (15 models × 10 columns)

        Impact:
        - Knowledge base for embedding model selection
        - Top picks: BGE-M3 (local), Cohere embed-v4.0 (cloud)
        - Critical: Nomic Embed must be replaced (English-only)

2026-07-20 15:00:11 +03:30

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Big Picture — All Embedding Models Comparison

Context

Domain: Insurance, Farsi-only
Pipeline: LangGraph + Qdrant (migrating from LlamaIndex + ChromaDB)
Current: Cloud = OpenAI text-embedding-3-large | Local = Nomic Embed (English-only ⚠️)
Hardware: 1× RTX 3090 (24 GB VRAM)

Executive Summary

After reviewing 15 embedding models across 5 cloud providers and 7 local options, the most promising candidates are:

BGE-M3 (local) — triple-mode retrieval, Farsi, 1.1 GB VRAM
Cohere embed-v4.0 (cloud) — strongest Farsi, 512K context, enterprise pricing
gte-multilingual-base (local) — lightest with Farsi, 610 MB VRAM

Critical: Nomic Embed (current local) is English-only and must be replaced.

Cloud Models

Model	Price/1M tokens	Context	Dims	Farsi	Source
text-embedding-3-large ⭐	$0.13	8,191	3072	Multilingual	openai.md
text-embedding-3-small	$0.02	8,191	1536	Multilingual	openai.md
embed-v4.0	Enterprise	512,000	1536	100+ langs ✅	cohere.md
voyage-4-large	$0.12	32,000	1024	Multilingual	voyage.md
voyage-4	$0.06	32,000	1024	Multilingual	voyage.md
Gemini Embedding	$0.15	8,192	768	Multilingual	google.md
text-embedding-004	~$0.10	8,192	768	Multilingual	google.md
text-multilingual-embedding-002	~$0.10	8,192	768	Multilingual	google.md
jina-embeddings-v3	~$0.02	8,192	1024	89 langs ✅	jina.md

⭐ = current cloud baseline

Local Models

Model	VRAM	Dims	Context	Farsi	ColBERT	Sparse	Serving	Source
BGE-M3 ⭐	1.1 GB	1024	8,192	✅ 100+	✅	✅	Ollama/TEI	bge-m3.md
gte-multilingual-base	610 MB	768	8,192	✅ 70+	❌	❌	TEI	gte-multilingual.md
multilingual-E5-large	1.1 GB	1024	512	✅ 100	❌	❌	Ollama/TEI	mE5-large.md
gte-Qwen2-1.5B	3 GB	1536	8,192	⚠️	❌	❌	TEI	—
e5-mistral-7B	14.2 GB	4096	512	⚠️	❌	❌	vLLM/TEI	—
MiniLM-L12-v2	235 MB	384	128	✅ 50+	❌	❌	Ollama	—
Nomic Embed ⚠️	274 MB	768	8,192	❌ EN only	❌	❌	Ollama	nomic.md
jina-embeddings-v3 (local)	1.1 GB	1024	8,192	✅ 89	✅	❌	TEI	jina.md

⚠️ = English-only (must replace)

Cost Comparison

Cloud Models (monthly estimate at 10M tokens/month)

Model	Cost/month	Notes
OpenAI text-embedding-3-large	$1.30	Current baseline
OpenAI text-embedding-3-small	$0.20	6.5× cheaper, lower quality
Cohere embed-v4.0	~$4-5/hr	Enterprise only
Voyage voyage-4-large	$1.20	200M free tokens first
Google Gemini Embedding	$1.50	Most expensive
Jina jina-embeddings-v3	$0.20	Cheapest

Local Models (monthly estimate)

All local models are free to run. The only cost is:

Electricity: ~$5-10/month for RTX 3090 running 24/7
Hardware: Already purchased (RTX 3090)
Ops time: One-time setup, then minimal maintenance

Recommendations

Decision	Recommendation	Fallback
Local model	BGE-M3	gte-multilingual-base
Cloud model	Cohere embed-v4.0	Voyage voyage-4-large
Serving platform	Ollama	TEI
Immediate action	Replace Nomic with BGE-M3	—

Pricing Sources

OpenAI: https://openai.com/api/pricing/
Cohere: https://cohere.com/pricing
Voyage AI: https://docs.voyageai.com/docs/pricing
Google Vertex: https://cloud.google.com/vertex-ai/generative-ai/pricing
Jina AI: https://jina.ai/pricing/

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