Llama or DeepSeek: which to run inside your own perimeter
Both families ship in Ollama and deploy on your own server. Llama starts at 1B, runs without a GPU, has Vision versions for images and the largest ecosystem of fine-tunes and tooling, but it uses its own Llama Community License with conditions on commercial use. DeepSeek starts at 7B and needs a GPU, yet its recent versions are MIT, context reaches 1M tokens and the catalog lists it for legal, finance and IT teams. The newest Llama in the catalog is Llama 4 from April 2025, while DeepSeek runs through V4.1-Flash in September 2026.
Comparison based on catalog data
| Parameter | Llama | DeepSeek |
|---|---|---|
| Category | Text, Image + text | Text, Image + text |
| Developer | Meta, USA | DeepSeek, China |
| Releases | Feb 2023 – Apr 2025 | Nov 2023 – Sep 2026 |
| Sizes | 1B – 405B | 7B – 1.6T-A49B |
| Hardware | Laptop, 1 GPU, Cluster | Laptop, 1 GPU, Cluster |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| License | Llama Community License | MIT (V2 and earlier versions: DeepSeek's own license prohibiting harmful use) |
| Russian | Not supported | Not stated |
| Ollama | Yes | Yes |
| Without GPU | Yes | No |
| Tasks |
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Choose Llama if
- You need a base for industry fine-tuning plus ready-made fine-tunes
- Hardware is modest: smaller Llama models run on a CPU from 1B up
- You need Vision versions to work with images
Choose DeepSeek if
- You want MIT with no conditions attached to commercial use
- You handle long contracts and reports: context runs up to 1M tokens
- You are building agents that call tools and APIs
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- Cohere Command or Llama: which to choose for a knowledge base
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- GigaChat or YandexGPT: which to choose for business
- gpt-oss or Qwen: which one to run on your own server
- Mistral or Qwen: which to choose for business
- Gemma or Phi: small models for modest hardware
Need a model for your task?
An open model can run on your own server: data stays in-house, there is no per-request fee, and the model can be fine-tuned on your documents.
- SelectThe model and size for your task and hardware budget
- DeployOn your server or in a closed network, with an API
- Fine-tuneOn your data, or connect a knowledge base
- IntegrateInto your CRM, ERP, bot, website or team chat