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What is an LLM VRAM Calculator?
An online Large Language Model (LLM) VRAM calculator estimates how much GPU memory is needed to run an LLM. With Overchat AI, you can simulate elastic load and use the interactive chat widget to see the real-world typing speed you will experience in your chatbot. This takes into account realistic KV cache build-up, context usage, and more. You can also see how the speed will be impacted if the model doesn't fit entirely into memory.
Our tool is against real Atomic Chat, vLLM, llama.cpp, and Hugging Face Transformers.
This way, you can select the largest model that will run smoothly on your system. First, choose your graphics card, iMac, or MacBook configuration. Then, select the model you want to run from the dropdown menu. Finally, drag the context and concurrent users sliders to set a realistic load. The dial on the right will indicate whether the model fits into memory and how the memory will be allocated. Scroll down to the chat simulation to see the realistic streaming speed of your chosen model on your hardware.
Features Of Our LLM Inference Calculator
Real-time VRAM breakdown. You can adjust the quantization, context length, and batch size to determine how many concurrent operations you want to run. The memory breakdown updates instantly. This allows you to see not only if your system can theoretically run a particular model, but also how it will perform in the real world and where bottlenecks will occur.
Overchat AI also shows generation speed in tokens per second and, time to first token — usethe chat simulation widget to see how it will feel to run the model on your systme in real life.
When a model is too large for a single card, the calculator offers a CPU offloading mode. With this mode, you can see how a model will perform with CPU/RAM offload. You'll notice that streaming speed and time to first tokens increase significantly, and you'll be able to decide if the additional wait time is acceptable.
The calculator comes with presets for many modern GPU cards from NVIDIA, as well as Apple Silicon devices. These range from basic M1 Macs to M5 Max and M4 Ultra.
