Jan vs Ollama
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
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Ollama
Run open-weight LLMs locally, with an optional paid cloud
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| RECATOOLS Score | 7.2 / 10 | 8.8 / 10 |
| Capability | ||
| Value for money | ||
| Ease of use | ||
| ASEAN readiness | ||
| API quality | ||
| Pricing | Open Source | Freemium |
| Free tier | Free and open source (Apache 2.0). Local models run offline; cloud connectors use your own provider API keys | Free, MIT-licensed local runtime with unmetered local use; free cloud account adds starter usage on starter models, with pay-as-you-go credits for all models |
| Paid from | — | Pro $20/mo or $200/yr ($60 usage incl.); Max $100/mo; Team $500/mo; Enterprise custom |
| Has API | ✓ | ✓ |
| Open source | ✓ | ✓ |
| Free to use | ✓ | ✓ |
| Users | — | — |
| Founded | 2023 | 2023 |
| Maker | Menlo Research Pte. Ltd. | — |
| Verdict | Jan is what many people mean by ChatGPT on their own laptop. It pulls GGUF models from Hugging Face and runs them offline through a bundled llama.cpp engine (MLX on Apple Silicon), and connectors for OpenAI, Anthropic, G... |
Ollama remains the easiest way to get an open-weight model running locally: one command pulls and serves a model, the API speaks OpenAI and Anthropic formats, and launch commands wire up Claude Code, Codex and OpenCode.... |
| Full review → | Full review → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.