BigBang1.1-35B-A3B-NPU2

BigBang1.1-35B-A3B-NPU2 (FastFlowLM / Lemonade NPU2 Quantization)

[!IMPORTANT] Quantization & NPU Compatibility Note: This repository contains Q4NX quantized weights converted from mradermacher/BigBang-v1-i1-GGUF to run natively on FastFlowLM (flm) v1.0.3+ and Lemonade on AMD XDNA NPU hardware.

• Model Type: Quantized model conversion (NPU Q4NX format)
• Parent / Base Model: mradermacher/BigBang-v1-i1-GGUF
• Details: Re-quantized with importance matrix (i1) for FastFlowLM v1.0.3+ and Lemonade on AMD XDNA NPU. Configured with verified ChatML EOS stop token handling.
• Architecture: BigBang-v1.1 (Qwen3.6 MoE 35B-A3B base with imatrix)
• Quantization Format: Q4_K_M (imatrix) / Q4NX
• Format: Q4NX (safetensors format with AMD NPU block packing). Note that this is not a standard GGUF file; it is executed natively via flm / Lemonade on AMD Ryzen AI NPUs.

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Serving with Lemonade & FastFlowLM

To serve this model via Lemonade or FastFlowLM:

# Pull and run with FLM:
flm pull BigBang1.1-35B-A3B-NPU2
flm serve BigBang1.1-35B-A3B-NPU2 --ctx-len 32768 --port 8001

Or configure via Lemonade:

lemonade run BigBang1.1-35B-A3B-NPU2

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Original Model Information (mradermacher/BigBang-v1-i1-GGUF)

Below is the model card from the upstream repository mradermacher/BigBang-v1-i1-GGUF:

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About

<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> <!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: -->

weighted/imatrix quants of https://huggingface.co/endless-frontier/BigBang-v1

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For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/BigBang-v1-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

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