# Sarvam-M 24B: RAM and VRAM requirements

> Sarvam-M 24B is a 24B Sarvam model. At Q4_K_M it needs about **16.3 GB** to run and fits **12 of 39** tracked devices. Minimum to run: Nvidia GeForce RTX 4090 (24GB).

Last validated: 2026-06-15. Sources: Ollama, HuggingFace GGUF repos, vendor specs.

## Memory by quantization
| Quant | On disk | To run (4k context) |
| --- | --- | --- |
| Q4_K_M | 14.3 GB | ~16.3 GB |
| Q8_0 | 25.1 GB | ~27.1 GB |
| FP16 | 47.2 GB | ~49.2 GB |

Memory = weights + KV cache + ~0.8 GB runtime overhead, and varies ±15% with context length.

## Will it run on my device?
- **Apple M1 (8GB)** (8 GB): No, not enough memory
- **Generic Android Phone (8GB RAM)** (8 GB): No, not enough memory
- **iPhone 17 Pro** (12 GB): No, not enough memory
- **Nvidia GeForce RTX 4080 (16GB)** (16 GB): No, not enough memory
- **Google Pixel 10 Pro** (16 GB): No, not enough memory
- **Nvidia GeForce RTX 4090 (24GB)** (24 GB): Yes, it runs
- **Apple M4 Pro (48GB)** (48 GB): Yes, it runs — room for Q8_0
- **Apple M3 Ultra (256GB)** (256 GB): Yes, it runs — room for FP16

Full table of all 39 devices: https://localmodel.run/model/sarvam-m-24b

## How to run
Use LM Studio (Mac/Windows) or Ollama / vLLM (Linux).

## Details
- Parameters: 24B
- Default context: 32k tokens
- License: Apache-2.0 (commercial use: yes)
- Released: 2025-05
- HuggingFace: 4,130 downloads/mo, 344 likes

## FAQ
### How much VRAM or RAM does Sarvam-M 24B need?
About 16.3 GB at Q4_K_M (weights 14.3 GB + KV cache + overhead) at a 4k context. Budget ~27.1 GB for Q8_0.
### Can Sarvam-M 24B run on a laptop?
Sarvam-M 24B is large; you need a high-memory Mac or a 24 GB+ GPU at Q4_K_M.
### Can I use Sarvam-M 24B commercially?
Yes, Apache-2.0 permits commercial use.

Sources: https://huggingface.co/sarvamai/sarvam-m, https://huggingface.co/lmstudio-community/sarvam-m-GGUF, https://huggingface.co/sarvamai/sarvam-m-q8-gguf
More: https://localmodel.run/model/sarvam-m-24b