Ollama Library · llama
Can I run orca-mini?
A general-purpose model ranging from 3 billion parameters to 70 billion, suitable for entry-level hardware.
Parameter counts and memory belong to each build below. A family can contain several sizes and tasks; fitting in memory is not a quality ranking.
Calculate memory for a build and contextorca-mini system requirements
Memory needed at 4K context, counting model weights, KV cache, compute buffers and runtime overhead. Download sizes come from the official Ollama registry.
| Build | Quantization | Download | Memory needed |
|---|---|---|---|
| orca-mini:3b3B parameters (tag)2K documented maximum contextThe displayed memory scenario exceeds this build's supported context.Build sourceCatalog checked 2026-10-13 | Q4_0 | 1.8 GB | ~3.7 GB |
| orca-mini:3b-q8_03B parameters (tag)2K documented maximum contextThe displayed memory scenario exceeds this build's supported context.Build sourceCatalog checked 2026-10-13 | Q8_0 | 3.4 GB | ~5.3 GB |
| orca-mini:7b-v2-q4_07B parameters (tag)2K documented maximum contextThe displayed memory scenario exceeds this build's supported context.Build sourceCatalog checked 2026-10-13 | Q4_0 | 3.6 GB | ~6.2 GB |
| orca-mini:7b7B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 3.6 GB | ~6.2 GB |
| orca-mini:7b-q4_07B parameters (tag)2K documented maximum contextThe displayed memory scenario exceeds this build's supported context.Build sourceCatalog checked 2026-10-13 | Q4_0 | 3.6 GB | ~6.2 GB |
| orca-mini:7b-v2-q4_K_M7B parameters (tag)2K documented maximum contextThe displayed memory scenario exceeds this build's supported context.Build sourceCatalog checked 2026-10-13 | Q4_K_M | 3.8 GB | ~6.5 GB |
| orca-mini:7b-v3-q4_K_M7B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 3.8 GB | ~6.5 GB |
| orca-mini:7b-q4_K_M7B parameters (tag)2K documented maximum contextThe displayed memory scenario exceeds this build's supported context.Build sourceCatalog checked 2026-10-13 | Q4_K_M | 3.8 GB | ~6.5 GB |
Showing the 8 smallest non-alias builds. Choose any build and change the context. A context above the build's documented maximum is a hypothetical calculation, not a supported setting.
How to run orca-mini locally
- 1.Install Ollama for Windows, macOS or Linux.
- 2.Download this exact build in a terminal:
ollama pull orca-mini:3b - 3.Check the source for the build's task. For text generation, run
ollama run orca-mini:3b. Base/text builds may need a prompt template; an instruct build is usually the appropriate starting point for a conversation.
Frequently asked questions about orca-mini
- How much VRAM do I need to run orca-mini?
- At 4K context, the smallest published build of orca-mini (Q4_0) needs roughly 3.7 GB of GPU memory once weights, KV cache, compute buffers and runtime overhead are counted. Bigger quantizations and longer context windows need more. It can also run partly or entirely on the CPU using system RAM, more slowly.
- Can I run orca-mini without a dedicated GPU?
- A supported CPU runtime can use system RAM. The smallest listed build needs an estimated 3.7 GB at 4K context, plus headroom for your operating system. Check the build's runtime requirements. We have not measured its speed on your CPU.
- How big is the orca-mini download?
- The smallest published build is 1.8 GB. There are 45 builds in total, the largest being 128.5 GB. Leave some extra free disk space beyond the download itself.
- How do I run orca-mini locally?
- Install Ollama, then download a specific build with "ollama pull orca-mini:3b". For a build that supports text generation, use ollama run with the same tag. Check the model source for its task and prompt format.
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Model data from the official Ollama registry · verified 13/10/2026