# Best local LLM for 512GB RAM or VRAM

URL: https://insidethemachine.ai/best/local-llm-for-512gb-ram
Data: models 2026-10-15, machines 2026-10-15. Source of scores: Artificial Analysis Intelligence Index (AA), LMArena. Not our own tests yet.
Usable memory assumed: 384 GB (75% of 512). Rule: min_memory_gb = weights_gb_4bit × 1.15 + 2. weights_gb_4bit = Q4_K_M file (Ollama, else HF GGUF) → MLX 4-bit (HF) → Ollama MLX/NVFP4 tag → Ollama default tag → params_total_b × 0.6 (flagged weights_estimated). +15% ≈ KV cache at ~8–16K context; +2GB runtime/process overhead. Long contexts (128K+) need much more.
Models that fit: 102 of 124.

## Top picks

| model | maker | AA index | needs (4-bit) | needs (8-bit) | run |
|---|---|---|---|---|---|
| GLM-5.3-Flash | Z.ai | 41.8 | 233 GB | 394.1 GB | MLX only |
| Qwen3.8-Flash-Next (125B-A6B) | Alibaba Qwen | 39.8 | 140 GB | 219.3 GB | `ollama run qwen3.8-flash-next:125b-a6b` |
| MiMo-V2.6-Flash | Xiaomi | 37.9 | 216.4 GB (est.) | - | - |
| Qwen3.8 27B | Alibaba Qwen | 33.7 | 22.7 GB | 36.5 GB | `ollama run qwen3.8:27b` |
| MiniMax M3 | MiniMax | 29.2 | 302.5 GB | 523.7 GB | MLX only |
| Nemotron 3.5 Super VL 120B-A12B | NVIDIA | 26.5 | 105.5 GB | 154.9 GB | `ollama run nemotron-3.5-super:120b-a12b` |

## By job

- Coding: GLM-5.3-Flash (233 GB, Terminal-Bench 2.1 84.3%) `mlx_lm.generate --model mlx-community/GLM-5.3-Flash-4bit --prompt 'hello'`
- Agents (tool use): GLM-5.3-Flash (233 GB) `mlx_lm.generate --model mlx-community/GLM-5.3-Flash-4bit --prompt 'hello'`
- Vision (reads images): GLM-5.3-Flash (233 GB)

## New at 512 GB (did not fit in 256 GB)

- GLM-5.3-Flash (233 GB, AA 41.8)
- MiMo-V2.6-Flash (216.4 GB, AA 37.9)
- MiniMax M3 (302.5 GB, AA 29.2)
- Qwen3.5 397B-A17B (282.7 GB, AA 21.4)
- Qwen3-Coder 480B-A35B (335.5 GB, AA 11.9)

## Machines with 512 GB

| machine | type | usable GB | models that fit | best fit | from (approx) |
|---|---|---|---|---|---|
| Mac Studio (M5 Ultra) | Mac desktop | 384 | 102 | GLM-5.3-Flash | $5,499 (2026-10-15) |

## Questions

**What is the best local LLM for 512 GB of RAM?**
GLM-5.3-Flash by Z.ai. It scores 41.8 on the Artificial Analysis Intelligence Index and needs about 233 GB at 4-bit. That is about 73% of Claude Opus 5.5 (57.6), the top paid model. Data as of 2026-10-15.

**How many local models fit in 512 GB?**
102 of the 124 text models in our data fit. We assume about 384 GB is usable for the model (75% of 512 GB), and a model needs its 4-bit file size × 1.15 + 2 GB.

**What is the biggest model that runs in 512 GB?**
Beam 1.0 501B A23B, 501.3B (23.4B active) parameters, needs about 347.9 GB at 4-bit. Bigger is not always smarter: GLM-5.3-Flash scores 41.8; Beam 1.0 501B A23B has no published score yet.

**What is the best coding model for 512 GB?**
GLM-5.3-Flash (needs 233 GB, Terminal-Bench 2.1 84.3%). Run it in a coding app like OpenCode or Cline. See https://insidethemachine.ai/best/local-coding-model.

**Does 512 GB of VRAM work the same as 512 GB of RAM?**
Close. On a Mac the memory is shared, and about 75% goes to the model. On a PC the graphics card's VRAM is what counts; we estimate VRAM minus 1 GB is usable, so a 512 GB card fits a little more than 512 GB of Mac memory. Models that spill out of VRAM into normal RAM run much slower.

More: https://insidethemachine.ai/models?tier=512 · https://insidethemachine.ai/machines?tier=512 · https://insidethemachine.ai/best