com.studiotvai/llm-vram · v1.0.0 · ai-and-media
StudioTV LLM VRAM Calculator is healthy: it completed an MCP handshake in 2875 ms and exposes 3 tools. It scores 59/100.
Does an LLM fit on your GPU? VRAM, KV cache and GPU count for any Hugging Face model.
Endpoint: https://studiotvai.com/api/mcp (streamable-http)
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| health | 17 / 25 |
| authEase | 15 / 15 |
| toolQuality | 15 / 15 |
| maintenance | 7 / 15 |
| adoption | 0 / 10 |
| usage | 0 / 10 |
| security | 5 / 10 |
Scoring v0.3, computed 2026-10-15T02:36:03.164Z.
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-14T22:05:50.290Z | Healthy | 2875 |
estimate_vram | GPU memory, number of GPUs, speed and rental cost to run an open LLM. Works for the models listed at https://studiotvai.com/api/models.json and any Hugging Face model id or link. Uses the real KV cache of each architecture (sliding window, hybrid linear attention, MLA). |
models_that_fit | Every listed open model that fits on the given GPU(s), largest first, with the most faithful weight format that fits. |
gpu_prices | Cheapest on-demand price per GPU-hour from AWS, Google Cloud, Azure, RunPod, Vast.ai, Oracle Cloud, OVHcloud, Scaleway, Verda, Akash and UpCloud, checked every hour. |