# Can I run Sarvam-105B on Apple M5 (32GB)?

> **No, not enough memory.** Needs ~67.5 GB even at Q4_K_M, but only ~21 GB is usable.

Last validated: 2026-06-15.

## Memory math
- Sarvam-105B: 105B (MoE, 10.3B active); Q4_K_M weighs 64.2 GB on disk.
- At Q4_K_M with a 4k context it needs ~67.5 GB (weights + KV cache + ~0.8 GB runtime overhead, ±15% with context length).
- Apple M5 (32GB): 32 GB unified, ~21 GB usable for model weights.
- Headroom: ~-46.5 GB.

## How to run
Recommended quant: n/a. Best tool on macOS: LM Studio.

## Run Sarvam-105B on other devices
- [Apple M4 Max (128GB)](https://localmodel.run/can-i-run/sarvam-105b/apple-m4-max-128gb)
- [Apple M5 Max (128GB)](https://localmodel.run/can-i-run/sarvam-105b/apple-m5-max-128gb)
- [Apple M3 Ultra (256GB)](https://localmodel.run/can-i-run/sarvam-105b/apple-m3-ultra-256gb)

## Other models that run on Apple M5 (32GB)
- [Qwen2.5 Coder 32B (32B)](https://localmodel.run/can-i-run/qwen2.5-coder-32b/apple-m5-32gb)
- [Granite 4.0 H Small (32B)](https://localmodel.run/can-i-run/granite-4.0-h-small/apple-m5-32gb)
- [Qwen3 30B-A3B (30.5B)](https://localmodel.run/can-i-run/qwen3-30b-a3b/apple-m5-32gb)
- [Gemma 2 27B (27B)](https://localmodel.run/can-i-run/gemma-2-27b/apple-m5-32gb)
- [Gemma 3 27B (27B)](https://localmodel.run/can-i-run/gemma-3-27b/apple-m5-32gb)
- [Mistral Small 3 24B (24B)](https://localmodel.run/can-i-run/mistral-small-3-24b/apple-m5-32gb)

Estimate, not a guarantee. Sources: https://huggingface.co/sarvamai/sarvam-105b, https://huggingface.co/sarvamai/sarvam-105b-gguf, https://www.sarvam.ai/blogs/sarvam-30b-105b.
More: https://localmodel.run/can-i-run/sarvam-105b/apple-m5-32gb