Can NVIDIA RTX 4070 Ti Super (16GB) run DeepSeek-V3-0324 671B (MoE)?

A single NVIDIA RTX 4070 Ti Super (16GB) cannot fit DeepSeek-V3-0324 671B (MoE) (378.7GB in Q4_K_M). You need 24x NVIDIA RTX 4070 Ti Super (384 GB total VRAM) for full GPU execution, or rent an A100/H100 80GB cloud instance.

How much VRAM does DeepSeek-V3-0324 671B (MoE) require in Q4_K_M, FP8, and FP16?

At 8,192 context length, DeepSeek-V3-0324 671B (MoE) requires 378.7 GB in GGUF Q4_K_M, 645.98 GB in FP8, and 1251.32 GB in FP16.

❌ 超出单卡显存上限 (NEEDS 24x NVIDIA RTX 4070 Ti Super)

DeepSeek-V3-0324 671B (MoE) on NVIDIA RTX 4070 Ti Super (16GB VRAM)

You need 24x NVIDIA RTX 4070 Ti Super (384 GB total VRAM) for full GPU execution, or rent an A100/H100 80GB cloud instance.

🎛️ 交互式显存、上下文长度与 CPU 卸载调优台

量化精度格式（基于 GGUF / AWQ 实测比特率 BPW）

推理引擎框架 (Runtime Engine)

上下文窗口长度 (Context Length) 8,192 tokens

并发批处理大小 (Batch Size) 1

KV Cache 缓存精度

多卡张量并行数量 (GPU Count)

系统内存卸载比例 (CPU Offload 层数占比) 0% (100% GPU)

📊 实时显存占用与推理吞吐遥测

378.7 GB / 16 GB

🟦 模型权重 (含词表层): 377.67 GB 🟪 KV Cache 缓存: 0.54 GB 🟨 引擎与算子工作区: 0.5 GB

所需显卡显存 (GPU VRAM)378.7 GB

所需系统内存 (CPU 卸载)0.00 GB

当前硬件可用显存16 GB (1x NVIDIA RTX 4070 Ti Super)

显存余量 / 溢出缺口-362.70 GB

预计生成速度 (Decode Speed)~2.8 tokens/sec

预计预填充速度 (Prefill Speed)~620 tokens/sec

4K 提示词首字延迟 (TTFT)~6609 ms

Transformer 层数与注意力头MLA-MoE (61L, 8/128 KV/Q heads)

🚀 一键复制启动命令 (vLLM / llama.cpp / Ollama)

ollama run deepseek-v3:671b
# Or llama.cpp server (8K context, Flash Attention):
llama-server -hf deepseek-ai/DeepSeek-V3-0324-GGUF -c 8192 -ngl 99 -fa

云显卡实时比价 & 租卡 vs 买卡回本计算器

本地显存不够？60 秒一键租用预装 vLLM/Ollama 的云端显卡 (DeepSeek-V3-0324 671B (MoE): 378.7 GB in 4-bit)

Recommended Cloud Tier: Multi-GPU H100 / H200 Node · Full FP16 Needs: 1251.32 GB

每天预计使用时长： 4 hrs/day

租卡对比买卡回本周期： ~32 months (vs $799 hardware)

Cloud Provider	RTX 4090 (24GB)	A100 (80GB)	H100 (80GB)	Est. Monthly Cost (4h/day)	Free Credit / Trial	Deploy
RunPod	$0.44 / hr	$1.39 / hr	$2.39 / hr	$52.80 / mo	Instant PyTorch / vLLM Templates + Serverless GPU	在 RunPod 一键部署 →
Vast.ai	$0.29 / hr	$0.95 / hr	$1.79 / hr	$34.80 / mo	Save 50–70% on RTX 4090 / 5090 / A100 rentals	租用低价显卡 →
Vultr Cloud GPU	—	$1.79 / hr	$2.69 / hr	$214.80 / mo (A100)	$300 Free Credit	领取 $300 免费算力 →
DigitalOcean GPU	—	—	$2.99 / hr	$358.80 / mo (H100)	$200 Free Credit (60d)	领取 $200 试用金 →

全量化精度档位显存与速度明细表: DeepSeek-V3-0324 671B (MoE) × NVIDIA RTX 4070 Ti Super

Quantization Format	Core / Emb BPW	Weights (GiB)	KV Cache (8K)	Total VRAM	1x NVIDIA RTX 4070 Ti Super (16GB)	Decode / Prefill	Min GPUs
FP16 / BF16 (Unquantized)	16 / 16	1249.83 GB	0.54 GB	1250.87 GB	显存不足 (+1234.9GB)	~1.2 / 620 tok/s	79x
FP8 (W8A8 / E4M3)	8.25 / 8.5	644.5 GB	0.54 GB	645.53 GB	显存不足 (+629.5GB)	~1.6 / 620 tok/s	41x
GGUF Q8_0 (8.50 bpw)	8.5 / 8.5	663.97 GB	0.54 GB	665.01 GB	显存不足 (+649.0GB)	~1.6 / 620 tok/s	42x
GGUF Q6_K (6.56 bpw)	6.56 / 6.56	512.43 GB	0.54 GB	513.46 GB	显存不足 (+497.5GB)	~2 / 620 tok/s	33x
GGUF Q5_K_M (5.69 bpw)	5.69 / 6.56	444.66 GB	0.54 GB	445.69 GB	显存不足 (+429.7GB)	~2.3 / 620 tok/s	28x
GGUF Q4_K_M / AWQ (4.83 bpw)	4.83 / 6.56	377.67 GB	0.54 GB	378.7 GB	显存不足 (+362.7GB)	~2.8 / 620 tok/s	24x
GGUF IQ4_XS (4.25 bpw)	4.25 / 5.5	332.26 GB	0.54 GB	333.29 GB	显存不足 (+317.3GB)	~3.1 / 620 tok/s	21x
GGUF Q3_K_M (3.91 bpw)	3.91 / 5	305.66 GB	0.54 GB	306.7 GB	显存不足 (+290.7GB)	~3.4 / 620 tok/s	20x

在其他显卡上测试该模型