Best local LLM for 48 GB.
Qwen3.8 27B is the smartest model that fits in 48 GB. It needs about 22.7 GB and is about 59% as smart as Claude Opus 5.5.
| Model | Maker | Score (AA) | Needs 4-bit | Needs 8-bit | Run it |
|---|---|---|---|---|---|
| Qwen3.8 27B | Alibaba Qwen | 33.7 | 22.7 GB | 36.5 GB | ollama run qwen3.8:27b |
| K2 Horizon MoVA 36B-A4B | IFM (MBZUAI) | 25.3 | 28.1 GB | 47.8 GB | MLX only (Mac) |
| Qwen3.5 27B | Alibaba Qwen | 22.9 | 21.5 GB | 36.5 GB | ollama run qwen3.5:27b |
| Qwen3.6 27B | Alibaba Qwen | 21.4 | 21.5 GB | 36.5 GB | ollama run qwen3.6:27b |
| Nemotron 3.5 Bolt 74B-A9B | NVIDIA | 21.4 | 30.7 GB | — | ollama run nemotron-3.5-bolt:74b-a9b |
| K2 Horizon 7B | IFM (MBZUAI) | 20.6 | 8.6 GB | 13 GB | MLX only (Mac) |
Pick by what you do.
What 48 GB adds over 32 GB.
| Model | Needs | Score (AA) |
|---|---|---|
| K2 Horizon MoVA 36B-A4B | 28.1 GB | 25.3 |
| Nemotron 3.5 Bolt 74B-A9B | 30.7 GB | 21.4 |
| Qwen3.5 35B-A3B | 27.3 GB | 19.3 |
| Qwen3.6 35B-A3B | 29.6 GB | 18.2 |
| Gemma 4 31B | 25 GB | 14.7 |
Computers and cards with 48 GB.
Graphics cards count VRAM, so they often fit a bit more.
| Machine | Type | Usable | Models that fit | Best fit | From (approx) |
|---|---|---|---|---|---|
| MacBook Pro 14"/16" (M5 Pro) | Mac laptop | 36 GB | 76 | Qwen3.8 27B | $2,499 · 2026-10-15 |
| MacBook Pro 14"/16" (M5 Max) | Mac laptop | 36 GB | 76 | Qwen3.8 27B | $4,099 · 2026-10-15 |
| Mac mini (M5 Pro) | Mac desktop | 36 GB | 76 | Qwen3.8 27B | $1,699 · 2026-10-15 |
| Mac Studio (M5 Max) | Mac desktop | 36 GB | 76 | Qwen3.8 27B | $2,499 · 2026-10-15 |
Short answers.
- What is the best local LLM for 48 GB of RAM?
- Qwen3.8 27B by Alibaba Qwen. It scores 33.7 on the Artificial Analysis Intelligence Index and needs about 22.7 GB at 4-bit. That is about 59% of Claude Opus 5.5 (57.6), the top paid model. Data as of 2026-10-15.
- How many local models fit in 48 GB?
- 76 of the 124 text models in our data fit. We assume about 36 GB is usable for the model (75% of 48 GB), and a model needs its 4-bit file size × 1.15 + 2 GB.
- What is the biggest model that runs in 48 GB?
- Nemotron 3.5 Bolt 74B-A9B, 74B (9B active) parameters, needs about 30.7 GB at 4-bit. Bigger is not always smarter: Qwen3.8 27B scores 33.7; Nemotron 3.5 Bolt 74B-A9B scores 21.4.
- What is the best coding model for 48 GB?
- Qwen3.8 27B (needs 22.7 GB, Terminal-Bench 2.1 79.8%). Run it in a coding app like OpenCode or Cline. See https://insidethemachine.ai/best/local-coding-model.
- Does 48 GB of VRAM work the same as 48 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 48 GB card fits a little more than 48 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 48GB RAM or VRAM URL: https://insidethemachine.ai/best/local-llm-for-48gb-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: 36 GB (75% of 48). 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: 76 of 124. ## Top picks | model | maker | AA index | needs (4-bit) | needs (8-bit) | run | |---|---|---|---|---|---| | Qwen3.8 27B | Alibaba Qwen | 33.7 | 22.7 GB | 36.5 GB | `ollama run qwen3.8:27b` | | K2 Horizon MoVA 36B-A4B | IFM (MBZUAI) | 25.3 | 28.1 GB | 47.8 GB | MLX only | | Qwen3.5 27B | Alibaba Qwen | 22.9 | 21.5 GB | 36.5 GB | `ollama run qwen3.5:27b` | | Qwen3.6 27B | Alibaba Qwen | 21.4 | 21.5 GB | 36.5 GB | `ollama run qwen3.6:27b` | | Nemotron 3.5 Bolt 74B-A9B | NVIDIA | 21.4 | 30.7 GB | - | `ollama run nemotron-3.5-bolt:74b-a9b` | | K2 Horizon 7B | IFM (MBZUAI) | 20.6 | 8.6 GB | 13 GB | MLX only | ## By job - Coding: Qwen3.8 27B (22.7 GB, Terminal-Bench 2.1 79.8%) `ollama run qwen3.8:27b` - Agents (tool use): Qwen3.8 27B (22.7 GB) `ollama run qwen3.8:27b` - Vision (reads images): Qwen3.8 27B (22.7 GB) ## New at 48 GB (did not fit in 32 GB) - K2 Horizon MoVA 36B-A4B (28.1 GB, AA 25.3) - Nemotron 3.5 Bolt 74B-A9B (30.7 GB, AA 21.4) - Qwen3.5 35B-A3B (27.3 GB, AA 19.3) - Qwen3.6 35B-A3B (29.6 GB, AA 18.2) - Gemma 4 31B (25 GB, AA 14.7) ## Machines with 48 GB | machine | type | usable GB | models that fit | best fit | from (approx) | |---|---|---|---|---|---| | MacBook Pro 14"/16" (M5 Pro) | Mac laptop | 36 | 76 | Qwen3.8 27B | $2,499 (2026-10-15) | | MacBook Pro 14"/16" (M5 Max) | Mac laptop | 36 | 76 | Qwen3.8 27B | $4,099 (2026-10-15) | | Mac mini (M5 Pro) | Mac desktop | 36 | 76 | Qwen3.8 27B | $1,699 (2026-10-15) | | Mac Studio (M5 Max) | Mac desktop | 36 | 76 | Qwen3.8 27B | $2,499 (2026-10-15) | ## Questions **What is the best local LLM for 48 GB of RAM?** Qwen3.8 27B by Alibaba Qwen. It scores 33.7 on the Artificial Analysis Intelligence Index and needs about 22.7 GB at 4-bit. That is about 59% of Claude Opus 5.5 (57.6), the top paid model. Data as of 2026-10-15. **How many local models fit in 48 GB?** 76 of the 124 text models in our data fit. We assume about 36 GB is usable for the model (75% of 48 GB), and a model needs its 4-bit file size × 1.15 + 2 GB. **What is the biggest model that runs in 48 GB?** Nemotron 3.5 Bolt 74B-A9B, 74B (9B active) parameters, needs about 30.7 GB at 4-bit. Bigger is not always smarter: Qwen3.8 27B scores 33.7; Nemotron 3.5 Bolt 74B-A9B scores 21.4. **What is the best coding model for 48 GB?** Qwen3.8 27B (needs 22.7 GB, Terminal-Bench 2.1 79.8%). Run it in a coding app like OpenCode or Cline. See https://insidethemachine.ai/best/local-coding-model. **Does 48 GB of VRAM work the same as 48 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 48 GB card fits a little more than 48 GB of Mac memory. Models that spill out of VRAM into normal RAM run much slower. More: https://insidethemachine.ai/models?tier=48 · https://insidethemachine.ai/machines?tier=48 · https://insidethemachine.ai/best