Best GPU for DeepSeek Hosting
DeepSeek’s models — V2 (16B/236B MoE), V3 (671B MoE), and DeepSeek-Coder — range from chatbot-friendly to compute-cluster scale. The right GPU depends on which variant you need.
The short answer: the RTX 5090 is the best GPU for self-hosting DeepSeek-V2 16B on a dedicated server. It has the right VRAM (32 GB) for the model, modern tensor cores, and the best cost-per-token in our catalogue for this workload.
Ranking — Best to Worst for This Workload
From best to worst for this specific workload, with the reason in plain English.
RTX 5090 Top Pick (V2 16B)
32 GB fits DeepSeek-V2 16B FP16 single-card with comfortable context.
32 GB · Blackwell · from £359/mo
RTX 6000 Pro 96 GB Top Pick (DeepSeek V2 large)
96 GB needed for DeepSeek-V2 236B (MoE) at INT4.
96 GB · Blackwell · from £1099/mo
RTX 3090 Budget Pick (V2 16B)
24 GB needs FP8 or INT4 for V2 16B. Workable but tight.
24 GB · Ampere · from £179/mo
A100 80 GB V3 / Cluster
DeepSeek V3 (671B MoE) needs multi-GPU A100 cluster. Talk to sales.
80 GB · Ampere · POA
RTX 5080 Coder 6.7B
16 GB fine for DeepSeek-Coder 6.7B FP16.
16 GB · Blackwell · from £189/mo
Background & Sizing
DeepSeek shipped some of the strongest reasoning models in the open-weight ecosystem. The V2 16B variant is the practical self-hosting target — it competes with much larger Llama variants thanks to the MoE architecture activating only 2.4B parameters per token.
DeepSeek family quick reference
- DeepSeek-V2 16B (Lite) — 32 GB FP16, ~10 GB INT4. Single-card on a 5090 or 6000 Pro.
- DeepSeek-V2 236B (full) — 470 GB FP16, sharded across multi-GPU cluster.
- DeepSeek-V3 671B — frontier-class, requires 8× H100 or comparable. POA build.
- DeepSeek-Coder 6.7B / 33B — coding-specialised. 6.7B fits 16 GB cards; 33B needs 5090 or 6000 Pro.
Frequently Asked Questions
The questions buyers actually ask before committing to a GPU server.
Is DeepSeek-V2 16B better than Llama 3 8B?
On reasoning benchmarks, often yes. DeepSeek’s MoE architecture punches above its weight at the cost of more VRAM.
Can I run DeepSeek-V3 on a single GPU?
No — 671B parameters do not fit any single GPU. Multi-node H100 cluster only.
DeepSeek-Coder vs Code Llama?
DeepSeek-Coder 6.7B is broadly competitive with Code Llama 13B at half the VRAM. Newer architecture, smaller, better.
Tool use support?
Yes — DeepSeek-V2 supports function calling. vLLM-compatible.
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