Best local LLM for 512 GB.
GLM-5.3-Flash is the smartest model that fits in 512 GB. It needs about 233 GB and is about 73% as smart as Claude Opus 5.5.
| Model | Maker | Score (AA) | Needs 4-bit | Needs 8-bit | Run it |
|---|---|---|---|---|---|
| GLM-5.3-Flash | Z.ai | 41.8 | 233 GB | 394.1 GB | MLX only (Mac) |
| 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 (Mac) |
| Nemotron 3.5 Super VL 120B-A12B | NVIDIA | 26.5 | 105.5 GB | 154.9 GB | ollama run nemotron-3.5-super:120b-a12b |
Pick by what you do.
What 512 GB adds over 256 GB.
| Model | Needs | Score (AA) |
|---|---|---|
| GLM-5.3-Flash | 233 GB | 41.8 |
| MiMo-V2.6-Flash | 216.4 GB | 37.9 |
| MiniMax M3 | 302.5 GB | 29.2 |
| Qwen3.5 397B-A17B | 282.7 GB | 21.4 |
| Qwen3-Coder 480B-A35B | 335.5 GB | 11.9 |
Computers and cards with 512 GB.
Graphics cards count VRAM, so they often fit a bit more.
| Machine | Type | Usable | Models that fit | Best fit | From (approx) |
|---|---|---|---|---|---|
| Mac Studio (M5 Ultra) | Mac desktop | 384 GB | 102 | GLM-5.3-Flash | $5,499 · 2026-10-15 |
Short answers.
- 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.
Scores are from Artificial Analysis and LMArena, not our own tests yet. Memory need = 4-bit file × 1.15 + 2 GB; a model fits when that is at most 75% of memory. Models 2026-10-15, machines 2026-10-15.
# 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