The Head-to-Head
| 8GB RAM | 16GB RAM | |
|---|---|---|
| Best models | 7B-class (Q4/Q5) | 7–14B (Q4–Q8) |
| Quality | Good — everyday chat, writing, summaries | Clearly better reasoning and nuance |
| Context window | Limited — memory gets tight | Comfortable for long documents |
| Document RAG | Workable for small corpora | Comfortable, room for the index |
| Multitasking | Close other apps while generating | Runs alongside normal work |
What Actually Fits in 8GB
8GB runs 7B-class models at Q4/Q5 quantization — roughly 4GB of weights, leaving room for the system and a modest context window. In practice that means:
- Qwen 7B, Llama 3.1 8B, Gemma 7B, and similar
- Solid performance on chat, drafting, summarizing, and light document work
- You'll close heavy browser tabs while generating and keep contexts short
It's genuinely usable — millions of people run exactly this. But it's the entry tier, not the sweet spot.
What 16GB Unlocks
16GB moves you into the 14B tier — models like Qwen 14B and Gemma 14B at Q4–Q8 — which is where local AI quality takes a visible step up: better reasoning, more nuanced writing, fewer obvious mistakes. You also get:
- A comfortable context window for long documents
- Room for a local vector store (document RAG) alongside the model
- The ability to keep your normal apps open while the model works
For most people, the 14B tier at 16GB is the best quality-per-dollar in local AI.
Model Picks for Each Tier
Best for 8GB: a 7B-class Q4 model — Qwen 7B or Llama 3.1 8B. See Top 10 GGUF Models Ranked by RAM for the full list with download links.
Best for 16GB: a 14B Q4–Q8 model — Qwen 14B or Gemma 14B. Full local RAG guidance for this tier is in Local RAG on 8GB RAM and the Mac-specific picks in Best Local AI Models for a 16GB MacBook.
The Verdict
If you already own an 8GB machine: don't rush out to upgrade. A 7B model is genuinely useful — start there and see how far it takes you.
If you're buying a machine for local AI: get 16GB. The 14B tier is where quality noticeably improves, and 16GB handles documents and multitasking far more comfortably. It's the difference between "local AI works" and "local AI is my daily driver."
For the full RAM discussion — including 32GB and beyond — see How Much RAM Do You Need to Run Local AI?
Frequently Asked Questions (FAQ)
Can I run local LLMs on 8GB RAM?
Yes. 8GB runs 7B-class Q4-quantized models — good for chat, drafting, and summarizing. You'll manage memory carefully: close heavy apps and use a smaller context window.
What's the real difference between 8GB and 16GB?
16GB unlocks 14B models (a clear quality step up), keeps more context in memory, and runs smoother with other apps open. 8GB works for a 7B model; 16GB is the recommended minimum if you're buying.
Which models fit 8GB RAM?
7B-class models quantized to Q4/Q5 — e.g., Qwen 7B, Llama 3.1 8B, Gemma 7B. They handle everyday chat, writing, and summarization well.
Which models fit 16GB RAM?
14B models at Q4-Q8 (e.g., Qwen 14B, Gemma 14B) and 7B models at higher quantization. This tier is the sweet spot for quality-per-RAM on laptops.
Should I upgrade from 8GB to 16GB?
If local AI matters to you, yes. The 14B tier is where quality noticeably improves, and 16GB also handles document RAG far more comfortably.
💻 Not sure what fits your machine?
I help people pick the right local AI setup for their hardware and work. Try GGUFLoader (free, open source) or contact me for a recommendation.