| # Hugging Face — the Hub's GPUs as bankML devices (addendum, 2026-09-29) |
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|
| An addendum to bankML's interaction with Hugging Face: bankML already imports models from the Hub (the importer's |
| catalogue and any Hugging Face GGUF, each pinned by the publisher's sha256), and since 0.2.12 its video-card |
| component lists the GPUs Hugging Face rents (`bankml gpu --remote`). This page records what those GPUs are, who |
| provisions them, and the news that changes who owns them. |
|
|
| ### The deal, as announced |
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| On **2026-09-02** NVIDIA entered a definitive agreement to acquire Hugging Face (NVIDIA Form 8-K, filed the same |
| week; confirmed publicly 2026-09-03). The terms are about **$11.9 billion** to Hugging Face stockholders plus an |
| equity retention program of up to about **$1.0 billion** for employees joining NVIDIA, reported as **$12.9 billion** |
| in all. ⚠ **It has not closed.** Closing is expected in the **first half of 2027**, subject to regulatory approvals, |
| so Hugging Face is still an independent company until then. |
| Sources: [NVIDIA 8-K](https://www.sec.gov/Archives/edgar/data/0001045810/000104581026000078/nvda-20260902.htm) · |
| [NVIDIA blog](https://blogs.nvidia.com/blog/nvidia-to-acquire-hugging-face/) · |
| [TechCrunch](https://techcrunch.com/2026/09/03/nvidia-confirms-it-will-buy-hugging-face-for-12-9-billion/) · |
| [CNBC](https://www.cnbc.com/2026/09/03/nvidia-agrees-to-buy-hugging-face-for-almost-13-billion-ai-expansion.html) · |
| [Bloomberg](https://www.bloomberg.com/news/articles/2026-09-03/nvidia-agrees-to-13-billion-deal-for-ai-platform-hugging-face) |
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| What changed is who will own the rented compute, and that the rented compute is, already, **all NVIDIA**. |
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| ### The provisioners and the hardware, read live today |
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| - **Provisioners.** Inference Endpoints' public provider list |
| (`GET https://api.endpoints.huggingface.cloud/v2/provider`) names **AWS** (eu-west-1, us-east-1, us-east-2, |
| us-west-2), **Azure** (eastus) and **GCP** (us-east4). |
| - **Jobs hardware** (`GET https://huggingface.co/api/jobs/hardware`, public, no token): **26 flavors, 22 of them |
| GPU**, every GPU an NVIDIA part. Prices are the API's per-minute figures × 60. |
|
|
| | flavor | GPUs | VRAM | $/h | |
| |---|---|--:|--:| |
| | t4-small / t4-medium | 1× T4 | 16 GB | 0.40 / 0.60 | |
| | l4x1 / l4x4 | 1× / 4× L4 | 24 / 96 GB | 0.80 / 3.80 | |
| | a10g-small / a10g-large | 1× A10G | 24 GB | 1.00 / 1.50 | |
| | a10g-largex2 / a10g-largex4 | 2× / 4× A10G | 48 / 96 GB | 3.00 / 5.00 | |
| | l40sx1 / l40sx4 / l40sx8 | 1× / 4× / 8× L40S | 48 / 192 / 384 GB | 1.80 / 8.30 / 23.50 | |
| | a100-large / a100x4 / a100x8 | 1× / 4× / 8× A100 | 80 / 320 / 640 GB | 2.50 / 10.00 / 20.00 | |
| | rtx-pro-6000 ×1 / ×2 / ×4 / ×8 | RTX PRO 6000 | 96 / 192 / 384 / 768 GB | 2.75 / 5.50 / 11.00 / 22.00 | |
| | h200 ×1 / ×2 / ×4 / ×8 | H200 | 141 / 282 / 564 / 1128 GB | 5.00 / 10.00 / 20.00 / 40.00 | |
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|
| - **Spaces hardware** (`GET https://huggingface.co/api/spaces/hardware`) lists 14 GPU flavors plus ZeroGPU (free, |
| dynamic). ⚠ **The Spaces list mislabels the L40S flavors:** `l40sx1/x4/x8` report `"model": "L4"` there, |
| while the Jobs list says L40S with the right memory (48/192/384 GB). Read the model from the Jobs list. |
|
|
| ### bankml sees them (bankml 0.2.12) |
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| bankml grew a video-card component (`bankML/gpu/`, a registry of backends with no crates). **`bankml gpu`** lists |
| the local cards through Vulkan, merged with the kernel's `/sys/class/drm` view. On this node that is a Radeon |
| Vega 3, and Mesa's llvmpipe is refused as a software renderer. **`bankml gpu --remote`** adds the Hugging Face |
| backend (`gpu/hf.rs`), which reads the Jobs hardware list above through the system `curl` (bankml has no TLS of its |
| own) and reports every GPU flavor as a **remote** device: its card count, memory and price per hour. A |
| multi-card flavor such as `h200x8` is one device with count 8. |
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|
| The rules, stated in code and tested: |
| - **A rented card is never selected automatically and never provisioned by bankml.** Listing costs nothing; |
| running costs money, and that is the owner's decision (mindX's cost doctrine for Hugging Face is in its `docs/HUGGINGFACE_INTEGRATION.md`). |
| - **Using one means running bankml where the card is:** a Hugging Face Job on the chosen flavor. There bankml's |
| Vulkan backend finds the NVIDIA card like any local one; NVIDIA's driver ships a Vulkan ICD. No CUDA toolkit is |
| needed. |
| - **Several cards share each matrix by rows**, so every output element stays one card's exact dot product. The |
| GPU kernels must reproduce bankml's CPU bits, which match llama.cpp's, on the card before they are trusted: a GPU |
| changes the speed, never the tokens. |
| - The CUDA Rust tracks of 2026-09-18 (`cutile-rs`, `cuda-oxide`, both Apache-2.0) remain the candidate for a |
| native NVIDIA backend module (`gpu/cuda.rs`) if Vulkan compute leaves speed on the table on these parts. |
| Vulkan comes first because it covers AMD and Intel as well, with nothing linked. |
|
|
| ### Where it stands (updated 2026-10-06) |
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|
| - Discovery is done: local cards via Vulkan and sysfs, remote cards via the Jobs API. |
| - The Q1_0 kernel is done in bankML's own SPIR-V: bit-exact against the CPU reference (0.2.13), working inside the |
| forward pass (0.2.14), and checked on each card by `bankml gpu --verify` before it is used. Since 0.3.7 |
| (unreleased) `BANKML_GPU_LIMIT` caps the card's share of memory and time, and each matrix shape is calibrated |
| between card and CPU ([modules/gpu.md](modules/gpu.md), CHANGELOG 0.3.7). The only card verified so far is the |
| integrated Radeon Vega 3. |
| - Q2_0 (ternary) and F16 still run on the CPU. Their GPU kernels, and the vendor matrix (AMD discrete, NVIDIA, |
| Intel), are in [TODO.md 0.5.0](TODO.md#050--hardware). |
| - A Job recipe that runs `bankml` on a chosen flavor, with its oracle on the card, comes with the first rented run. |
| - No money has been spent and none will be spent without the owner starting a Job. |
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