freakyskittle/NVIDIA-Nemotron-3.5-Bolt-74B-DERISKED-GGUF
AI model by freakyskittle
Older snapshot: check the original source for current information.
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
GGUF conversions of Blackfrost-AI/NVIDIA-Nemotron-3.5-Bolt-74B-DERISKED-BF16, a 74B-parameter hybrid mamba / MoE reasoning model with a RADIO vision tower, aimed at security operations, detection engineering, incident response, and malware analysis. Every trunk below passed a short Vulkan generation test on consumer hardware (AMD Radeon 680M, 16 GB shared) before it was uploaded. Each NAME.py file beside its .gguf is that test's transcript, including the Python function the model was asked to write. Nothing was uploaded untested. NemotronHOmniReasoningV3 (nemotronhomni): The expert count varies per block: 240, 304, 368, 432 or 496. These GGUFs carry a per-layer expertcount array instead of one global scalar, alongside the per-layer expertusedcount and expertfeedforwardlength arrays that Puzzle-style models already use. Upstream llama.cpp reads expertcount as a single u32, so until per-layer expert counts land upstream, use a build that supports them (the fork these were produced with). The trunk is otherwise stock nemotronhmoe. mmproj-NVIDIA-Nemotron-3.5-Bolt-74B-DERISKED-f16.gguf holds the vision tower:…
Read the full model card ↗ · Preview checked 2026-10-29T01:42:44.684Z
Inside the original model card — Document outline
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Documentation belongs to its respective authors. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
freakyskittle/NVIDIA-Nemotron-3.5-Bolt-74B-DERISKED-GGUF is a task-unspecified model repository published by freakyskittle on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- Not reported
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2026-10-17T06:23:34.000Z
- Last modified
- 2026-10-17T06:23:34.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-17T06:42:57.152Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.