bots.st/nodegrove-vram-can-i-run-it
Nodegrove VRAM: can I run it?
Estimate VRAM needs and fitting GPUs
2142 ms
answered our call
- State
- Answered
- Protocol
- MCP 2025-06-18
- Tools listed
- 6
- Answered
- 3 of the last 3 calls
How to reach it
- MCP, HTTP
https://mcp.nodegrove.io/mcp - npm
npx -y @nodegrove/vram-mcpReleased 3 Nov 2026, version 1.1.5
What it can do
| Tool | What it says it does |
|---|---|
can_i_run | Can this GPU run this open-weight LLM? Returns fits, tight or no, the memory split (weights, KV cache, overhead), a decode-speed ceiling, the longest context that fits and, on a no, every change that would make it fit: quantisation, KV cache, context, another card or a smaller model. Model: a name… |
estimate_from_hf_repo | Reads any Hugging Face model repo's config.json and parameter count and estimates its memory: the attention layout found (standard, sliding-window, hybrid or latent), how much each 1,000 tokens of context costs, and weights + KV cache + overhead at every quantisation. For models nodegrove.io has… |
estimate_vram | How much memory an LLM needs: weights + KV cache + overhead at each quantisation (or one), at a given context, and the smallest common card class that holds each. Model: a name or id from list_models, any Hugging Face repo id, or its architecture (params_b, layers, kv_heads, head_dim). |
list_gpus | The GPUs and machines nodegrove.io covers: memory, the memory a runtime can use and bandwidth, from the makers' specs, with each one's page. |
list_models | The open-weight LLMs nodegrove.io has verified against their config.json (data version 2026-11-03): id, size, attention design, native context, licence, memory at Q4 with 8k context and each model's page. |
what_fits | Which open-weight LLMs fit this GPU: every model in list_models checked at one quantisation and context, with a recommended everyday model (the biggest class that fits with room for context at conversational speed), the largest that fits, the best at Q8 and the first out of reach. GPU: a name or… |
In its maker's words
Can this LLM run on my GPU? VRAM, speed ceiling and what fits instead, for any model and GPU.
- Website
- nodegrove.io/mcp
- Source
- github.com/nodegrove/vram-mcp
- Publisher
- nodegrove.io
- Listed from
- the official MCP Registry as
io.nodegrove/vram-mcp - Version
- 1.1.5, updated 3 Nov 2026
- Kinds of work
- AI models and agent tools, Health and science, Search and research
The domain it lives on
- nodegrove.io
- registered 8 Sep 2026 (2 months ago), at NAMECHEAP INC, its home page is a working site
From our own crawl of domain names: registry records and the home page as our crawler last saw it.
Every call we made
| When | What happened | Time |
|---|---|---|
| Answered | 2142 ms | |
| Answered | 2658 ms | |
| Answered | 516 ms |
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