Inside The Machine
48 GB · 76 models fit · data 2026-10-15

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.

Top picks for 48 GB, about 36 GB usable. AA = Artificial Analysis Intelligence Index; Claude Opus 5.5 = 57.6.
ModelMakerScore (AA)Needs 4-bitNeeds 8-bitRun it
Qwen3.8 27BAlibaba Qwen33.722.7 GB36.5 GBollama run qwen3.8:27b
K2 Horizon MoVA 36B-A4BIFM (MBZUAI)25.328.1 GB47.8 GBMLX only (Mac)
Qwen3.5 27BAlibaba Qwen22.921.5 GB36.5 GBollama run qwen3.5:27b
Qwen3.6 27BAlibaba Qwen21.421.5 GB36.5 GBollama run qwen3.6:27b
Nemotron 3.5 Bolt 74B-A9BNVIDIA21.430.7 GB—ollama run nemotron-3.5-bolt:74b-a9b
K2 Horizon 7BIFM (MBZUAI)20.68.6 GB13 GBMLX only (Mac)
By job

Pick by what you do.

CodingQwen3.8 27B

Needs 22.7 GB. Terminal-Bench 2.1: 79.8%.

ollama run qwen3.8:27b
Agents (uses tools)Qwen3.8 27B

Needs 22.7 GB.

ollama run qwen3.8:27b
Reads imagesQwen3.8 27B

Needs 22.7 GB.

ollama run qwen3.8:27b
New at 48 GB

What 48 GB adds over 32 GB.

ModelNeedsScore (AA)
K2 Horizon MoVA 36B-A4B28.1 GB25.3
Nemotron 3.5 Bolt 74B-A9B30.7 GB21.4
Qwen3.5 35B-A3B27.3 GB19.3
Qwen3.6 35B-A3B29.6 GB18.2
Gemma 4 31B25 GB14.7
Machines

Computers and cards with 48 GB.

Graphics cards count VRAM, so they often fit a bit more.

Prices are approximate and dated. 2026 prices are inflated by the memory-chip shortage.
MachineTypeUsableModels that fitBest fitFrom (approx)
MacBook Pro 14"/16" (M5 Pro)Mac laptop36 GB76Qwen3.8 27B$2,499 · 2026-10-15
MacBook Pro 14"/16" (M5 Max)Mac laptop36 GB76Qwen3.8 27B$4,099 · 2026-10-15
Mac mini (M5 Pro)Mac desktop36 GB76Qwen3.8 27B$1,699 · 2026-10-15
Mac Studio (M5 Max)Mac desktop36 GB76Qwen3.8 27B$2,499 · 2026-10-15
Questions

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.

AGENT VIEW · text/markdown · or send Accept: text/markdown
# 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