Shanghai AI Laboratory · internlm2
Can I run internlm2?
InternLM2.5 is a 7B parameter model tailored for practical scenarios with outstanding reasoning capability.
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 contextinternlm2 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 |
|---|---|---|---|
| internlm2:1.8b1.8B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 1.0 GB | ~1.9 GB |
| internlm2:1.8b-chat-v2.5-q4_K_M1.8B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 1.1 GB | ~2.0 GB |
| internlm2:1.8b-chat-v2.5-q5_K_M1.8B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q5_K_M | 1.3 GB | ~2.2 GB |
| internlm2:1.8b-chat-v2.5-q6_K1.8B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q6_K | 1.4 GB | ~2.3 GB |
| internlm2:1.8b-chat-v2.5-q8_01.8B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q8_0 | 1.9 GB | ~2.8 GB |
| internlm2:1.8b-chat-v2.5-fp161.8B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | F16 | 3.5 GB | ~4.6 GB |
| internlm2:7b7B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 4.1 GB | ~5.4 GB |
| internlm2:1m1M parameters (tag)256K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 4.1 GB | ~5.4 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 internlm2 locally
- 1.Install Ollama for Windows, macOS or Linux.
- 2.Download this exact build in a terminal:
ollama pull internlm2:1.8b - 3.Check the source for the build's task. For text generation, run
ollama run internlm2:1.8b. Base/text builds may need a prompt template; an instruct build is usually the appropriate starting point for a conversation.
Frequently asked questions about internlm2
- How much VRAM do I need to run internlm2?
- At 4K context, the smallest published build of internlm2 (Q4_0) needs roughly 1.9 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 internlm2 without a dedicated GPU?
- A supported CPU runtime can use system RAM. The smallest listed build needs an estimated 1.9 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 internlm2 download?
- The smallest published build is 1.0 GB. There are 24 builds in total, the largest being 37.0 GB. Leave some extra free disk space beyond the download itself.
- How do I run internlm2 locally?
- Install Ollama, then download a specific build with "ollama pull internlm2:1.8b". 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