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Editorial ranking · 2026

Best local LLM for mac 8gb

Top 7 open-source picks for mac 8gb, ranked by benchmark performance and real-world fit. Updated monthly.

#1

Pleias-RAG 1B

1.2B · PleIAs · Apache 2.0

A 1.2B RAG-specialized model from PleIAs with built-in citation and grounding behavior. Beats most sub-4B small language models on HotPotQA.

VRAM Q4: 0.8 GB · Context: 2k
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#2

DeepSeek R1 Distill Qwen 1.5B

1.5B · DeepSeek · MIT

DeepSeek's R1 reasoning distilled into a 1.5B MIT-licensed model with visible chain-of-thought. Hits MATH-500 83.9 and runs on any laptop.

VRAM Q4: 1 GB · Context: 128k
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#3

CroissantLLM 1.3B

1.3B · CroissantLLM · MIT

A 1.3B bilingual French/English model from Sorbonne's MLIA lab, light enough to run on a CPU and shipped with a fully auditable training corpus.

VRAM Q4: 1 GB · Context: 2k
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#4

SmolLM2 1.7B Instruct

1.7B · HuggingFace · Apache 2.0

HuggingFace's 1.7B Apache 2.0 instruct model trained on 11T tokens. Beats Qwen2.5-1.5B by roughly 6 points on MMLU-Pro, making it a top pick at the sub-2B tier.

VRAM Q4: 1.2 GB · Context: 8k
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#5

Qwen 2.5 Coder 1.5B Instruct

1.5B · Alibaba · Apache 2.0

Alibaba's smallest Qwen 2.5 Coder at 1.5B parameters under Apache 2.0, covering 92 programming languages. HumanEval 70.7 makes it a serious on-device completion model.

VRAM Q4: 1 GB · Context: 32k
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#6

SmolVLM2 2.2B Instruct

2.2B · HuggingFace · Apache 2.0

HuggingFace's 2.2B vision-language model built on SmolLM2-1.7B, handling image, video, and text in roughly 5.2GB of VRAM. The smallest serious VLM with video understanding.

VRAM Q4: 1.6 GB · Context: 8k
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#7

Granite 4.0 3B Vision

3B · IBM · Apache 2.0

IBM's 3B vision-language model purpose-built for enterprise document extraction, including OCR, table parsing, and form understanding. Apache 2.0 and laptop-deployable.

VRAM Q4: 2.2 GB · Context: 16k
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