# Run it locally

> A series on running open-weight models locally: Muse Spark Open, Kimi K3, GLM-5.3-Flash and Qwen3.8-27B, with the hardware, memory, speed and cost of each against the API.

- Canonical: https://www.anchorterminal.com/blog/run-it-locally/
- Markdown: https://www.anchorterminal.com/blog/run-it-locally/index.md (~300 tokens)
- Slim: https://www.anchorterminal.com/blog/run-it-locally/index.min.md (~230 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/blog/run-it-locally/index.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.
- Updated: 2026-10-17

- [Can you run Muse Spark Open locally? Hardware, RAM and cost](https://www.anchorterminal.com/blog/run-muse-spark-open-locally.md), 2026-10-15, Run it locally, 9 min read. Vlad Cealicu on Meta's local pitch for Muse Spark Open (816B, 42B active), and how to run it locally. How much RAM and VRAM each version needs, whether it runs on a Mac Studio, a Minisforum MS-S1 Max, RTX 5090s, a DGX Spark or a CPU server, how many of each you'd need, what they cost and how fast they'd be, and when an API is cheaper.

RSS: https://www.anchorterminal.com/blog/run-it-locally/feed.xml

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp