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Run LLM Locally

DeepSeek R1 Distill Llama 70B on the H100 PCIe

With 80 GB of VRAM, the H100 PCIe runs DeepSeek R1 Distill Llama 70B at Q4_K_M entirely on the GPU with an 8K context (about 45.1 GB needed). At Q8_0 it fits entirely.

DeepSeek R1 Distill Llama 70B

Q4_K_M · 8K context

Excellent

The model needs about 45.1 GB and fits in the 77.6 GB available, with 32.5 GB to spare.

Your hardware
H100 PCIe 80 GB · 64 GB RAM
Estimated memory
~45.1 GB estimate
VRAM (usable memory)
77.6 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
30–42 tok/s estimate
Largest context in fast memory
107K tokens
Confidence: low

Based on: memory bandwidth (2,000 GB/s) and model size

Memory breakdown

~45.1 GB (43.9 GB–46.3 GB) needed · estimate

Fits entirely in VRAM · 32.5 GB left

  • Model weights39.6 GB
  • KV cache2.5 GB
  • Runtime overhead0.8 GB
  • Safety margin2.1 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (CUDA) · flash attention on · weights = real file size

EstimateData updated 24 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card

What makes this estimate less reliable

  • no benchmark for this hardware and model yet

Other quantizations on the H100 PCIe

DeepSeek R1 Distill Llama 70B on H100 PCIe + 64 GB RAM · 8K context
DeepSeek R1 Distill Llama 70B Q8_08K~76.8 GB · 19–25 tok/s estimateCompatible with limits
DeepSeek R1 Distill Llama 70B Q6_K8K~60.1 GB · 23–32 tok/s estimateExcellent
DeepSeek R1 Distill Llama 70B Q5_K_M8K~52.3 GB · 26–36 tok/s estimateExcellent
DeepSeek R1 Distill Llama 70B Q4_K_M8K~45.1 GB · 30–42 tok/s estimateExcellent
DeepSeek R1 Distill Llama 70B IQ4_XS8K~40.6 GB · 33–47 tok/s estimateExcellent
DeepSeek R1 Distill Llama 70B Q3_K_M8K~37 GB · 36–51 tok/s estimateExcellent

Alternatives

Hardware that runs DeepSeek R1 Distill Llama 70B Q4_K_M entirely in memory

Prices and links follow the market you choose.

RTX 6000 Ada Generation

NVIDIA

CompatibleRuns DeepSeek R1 Distill Llama 70B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

Radeon PRO W7900

AMD

CompatibleRuns DeepSeek R1 Distill Llama 70B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

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AMD Ryzen AI Max+ 395

Unified memory PC

CompatibleRuns DeepSeek R1 Distill Llama 70B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

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No current offer imported for this market: the link opens a marketplace search.

Frequently asked questions

Can the H100 PCIe run DeepSeek R1 Distill Llama 70B?
The model needs about 45.1 GB and fits in the 77.6 GB available, with 32.5 GB to spare.
Which quantization should I use on the H100 PCIe?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~76.8 GB / 77.6 GB.
What is the largest context on the H100 PCIe?
At Q4_K_M, about 107K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is DeepSeek R1 Distill Llama 70B (H100 PCIe)?
We estimate 30–42 tok/s (estimate, confidence low). Based on: memory bandwidth (2,000 GB/s) and model size.