LLM Inference VRAM & GPU Requirement Calculator

Accurately calculate how many GPUs you need to deploy LLMs. Supports NVIDIA, AMD, Huawei Ascend, Mac M-series. Get instant hardware requirements.

Model Selection

Model Parameters (Billions)

Precision

Average Context Length

GPU Model

Concurrent Users

Expected Experience Per User

token/s

GPU Count

GPUs

Memory Requirements 673.99 GB

Requires 9 GPUs (based on memory capacity)

Model Memory

671 GB

All model weights

KV Cache

0.5 GB

Conversation history cache

Activation Memory

2.07 GB

Expert model optimization

Computation Cache

0.41 GB

Temporary computation cache

Throughput Requirements 10 tokens/s

Requires 9 GPUs (based on VRAM bandwidth & computing performance)

Total Throughput

1,042 tokens/s

Total computing power of all GPUs

Throughput Per User

1,042 tokens/s

Total throughput ÷ 1 users

✅ Meets expectation 10 token/s

Estimated Latency

96 ms

100 tokens average response time

Scenario Examples (GPU + Model + Concurrency):

Click these examples to quickly configure popular model deployment scenarios!