Can OvisOCR2 0.8B run on MacBook Air M3 24GB?
What this means
OvisOCR2 0.8B fits on the MacBook Air M3 · 24GB at Q4_K_M. We estimate it uses 1.5GB of the conservative 21GB working budget.
Estimated decode speed is 70–96.7 tokens/s. A roughly 300-word answer may take around 5 seconds.
See how fast it feels
Using the midpoint of our 70–96.7 tokens/s estimate for this demo.
Where the memory goes
| Component | Detail | GB |
|---|---|---|
| Model weights | Q4_K_M GGUF (0.6 GB) + mmap overhead | 0.6 |
| KV cache | 4K context window | 0.1 |
| Runtime | macOS inference app + compute buffers | 0.8 |
| Total needed | at Q4_K_M, 4K context | 1.5 |
| Working budget | 24 GB unified memory − conservative macOS reserve | 21 |
| Headroom | remaining inside the working budget | 19.5 |
Pick your quant
| Quant | Download | Memory | Estimated speed | Verdict |
|---|---|---|---|---|
| Q2_K | 0.4 GB | 1.3 GB | ~105–145 tok/s | ✓ Runs great |
| IQ4_XS | 0.5 GB | 1.4 GB | ~84–116 tok/s | ✓ Runs great |
| Q3_K_M | 0.5 GB | 1.4 GB | ~84–116 tok/s | ✓ Runs great |
| Q4_0 | 0.5 GB | 1.4 GB | ~84–116 tok/s | ✓ Runs great |
| Q4_K_S | 0.5 GB | 1.4 GB | ~84–116 tok/s | ✓ Runs great |
| Q4_K_M ★ | 0.6 GB | 1.5 GB | ~70–96.7 tok/s | ✓ Runs great |
| Q5_K_M | 0.6 GB | 1.5 GB | ~70–96.7 tok/s | ✓ Runs great |
| Q6_K | 0.7 GB | 1.6 GB | ~60–82.9 tok/s | ✓ Runs great |
| Q8_0 | 0.8 GB | 1.7 GB | ~52.5–72.5 tok/s | ✓ Runs great |
Use this model for its intended task
OvisOCR2 0.8B is designed to turn document-page images into structured Markdown, including text, tables, and formulas. This Mac has enough working memory for the tracked Q4_K_M weights, but loading the file in a plain chat window does not supply the inputs, tools, or action loop that make the model useful.
It documents the intended workflow and supported developer runtimes. This is not yet a point-and-click setup for beginners, so do not install LM Studio expecting an ordinary chat tutorial to reproduce the model's task.
Choose Qwen3 0.6B instead. Its page gives the complete graphical install, download, first prompt, and offline check.
This model is designed to turn document-page images into structured Markdown, including text, tables, and formulas. Its weights may fit in memory, but it needs an OCR workflow that can send page images through the model—not a text-only chat window. A normal LM Studio chat does not provide that workflow.
Other models on this Mac
OvisOCR2 0.8B on other MacBook Air M3 configurations
FAQ
Can the MacBook Air M3 · 24GB run OvisOCR2 0.8B?
Yes at Q4_K_M. We estimate about 1.5GB of working memory and 70–96.7 tokens/s at 4K context.
Which OvisOCR2 0.8B quant should I use on this Mac?
Q4_K_M. It is a 0.6GB download and leaves about 19.5GB inside our conservative working budget.
Which app should I use for OvisOCR2 0.8B on this Mac?
OvisOCR2 0.8B is a task-specific model, not a normal local chat download. The selected weights fit this Mac, but the model still needs its publisher's intended workflow. This page links that repository and recommends Qwen3 0.6B if you just want local chat.
Are these speeds measured on a MacBook Air M3?
No. The range is a formula estimate based on memory bandwidth, model size, active parameters, cooling, and a 4K context. The app, backend, thermals, and prompt can change real performance.