Model Hosting Guide

Cheapest Cloud GPU to Host BGE / E5 Vector Embedding Fleet

Vector embedding models (BGE, E5, GTE) are encoder-only transformers that produce dense vector representations for semantic search and RAG pipelines. At FP16 (4-16 GB per model), the L40S (48 GB) can host 3-10 models concurrently for multi-tenant workloads.

ParametersMulti-Model Dense Vector Batch

Min GPUL40S

Min VRAM16 GB - 48 GB

Cluster1x L40S 48GB (High PCIe bandwidth)

VRAM Sizing Matrix

Memory consumption at different quantization levels for BGE / E5 Vector Embedding Fleet. Includes model weights only — KV-cache adds 2-32 GB depending on context length and batch size.

Precision	VRAM Required	Fits On	Quality Loss
FP16 / BF16	4 GB - 16 GB	Single GPU with headroom	None (full precision)
FP8	2 GB - 8 GB	Single GPU	<1% perplexity delta
INT4 / AWQ	N/A	Single consumer GPU	1-3% quality degradation

Hardware Bottleneck Advice

KV-cache expansion, tensor parallelism constraints, and production considerations for BGE / E5 Vector Embedding Fleet.

KV-Cache & Context Scaling

Embedding models are encoder-only — no KV-cache. The L40S (48 GB) can host 3-10 embedding models simultaneously for multi-tenant vector search workloads.

Tensor Parallelism

TP=1 per model. Embedding models are small (335M-1.5B params). The L40S hosts multiple models concurrently via model multiplexing.

Live Cloud Pricing for L40S

Filtered to L40S-class hardware — the recommended GPU for hosting BGE / E5 Vector Embedding Fleet.

Provider	GPU & VRAM	Interconnect	Spot Rate	On-Demand	Monthly	Status	Action
Vast.ai Community	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$0.69 / hr	$1.73 / hr	$422 / mo	Instant	Deploy →
RunPod Cloud	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$1.09 / hr	$2.73 / hr	$667 / mo	Instant	Deploy →
Spheron Bare Metal	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$1.19 / hr	$2.97 / hr	$728 / mo	Instant	Deploy →
Lambda Labs Dedicated	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$1.49 / hr	$3.73 / hr	$912 / mo	Instant	Deploy →

Data Freshness: Public Cloud APIs & Market Scraping | Refreshed Daily (UTC)|Benchmark Baseline: Ubuntu 24.04, CUDA 12.4, vLLM v0.6.x, PagedAttention v2, FlashAttention-3

Production Runbook

Ready-to-deploy vLLM / SGLang launch command for BGE / E5 Vector Embedding Fleet.

terminal

text-embeddings-router --model-id BAAI/bge-large-en-v1.5 --port 8080 --max-batch-tokens 16384

Recommended GPU: L40S

Cluster Config: 1x L40S 48GB (High PCIe bandwidth)

Min VRAM: 16 GB - 48 GB

Related hosting guides

H10

DeepSeek V2 / V2.5236B MoE (21B active)

H20

Meta Llama 3.3 70B Instruct70.6B Dense

L40

Mistral NeMo 12B12.2B Dense (128k context)