The hybrid quant employs different quantization levels on a per layer basis to enable both high performance and small file size at the same time. The quants employed are all K to avoid slow CPU or older GPU processing of IQ quants. Three quants are available for the model as follows:

Q3_S_H : Smallest Q3_K based quant available

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   ]'
  FLAGS="--token-embedding-type Q4_K --output-tensor-type Q5_K --layer-types-high"

Q3_K_H : Slightly larger Q3_K based quant

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  FLAGS="--token-embedding-type Q4_K --output-tensor-type Q5_K --layer-types-high"

Q4_K_H : Largest and best performance quant

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   ]'
   FLAGS="--token-embedding-type Q4_K --output-tensor-type Q6_K"

All three quants were optimized to maintain knowledge preservation and reasoning performance using a small set of curated test/evaluation prompts. All three quants score 100% on the eval prompts but the Q3 quants sometimes get a little goofy, giving wrong answer then correcting itself with the right one, or adding some non sequiter with the answer etc. Q4_K_H is rock solid. Note that use of Q2_K or Q2_K_S was not possible with this model since any Q2 use even at deep layers threw the model immediately into either noncoherence or large knowledge loss.

Comparison:

Quant	size	PPL	Comment
Q3_S_H	32.6e9	4.8	Q3_K dominant with Q4_K embedding
Q3_K_H	33.4e9	4.8	" "
Q3_K_M	34.3e9	4.9	Fails parts of eval prompt set
Q4_K_H	37.5e9	4.5	Best available quant
IQ4_XS	38.3e9	4.4	Q4_K embedding Q6_K output

Usage:

This model may be used together with fixie-ai ultravox-v0_5-llama-3_3-70b or ultravox-v0_6-llama-3_3-70b to enable it to process audio (.mp3 and .wav files) and text inputs and generate text outputs. The mmproj file are made available here: https://huggingface.co/steampunque/ultravox-v0_5-llama-3_3-70b-Hybrid-GGUF , https://huggingface.co/steampunque/ultravox-v0_6-llama-3_3-70b-MP-GGUF More information about running multimedia may be found in the docs in the mtmd readme in the tools directory of the llama.cpp source tree https://github.com/ggml-org/llama.cpp/blob/master/tools/mtmd/README.md.

Benchmarks:

A partial set of benchmarks for the model will eventually be given here: https://huggingface.co/spaces/steampunque/benchlm

Download the file from below:

Link	Type	Size/e9 B	Notes
Llama-3.3-70B-Instruct.Q3_S_H.gguf	Q3_S_H	32.6e9 B	1.7B smaller than Q3_K_M
Llama-3.3-70B-Instruct.Q3_K_H.gguf	Q3_K_H	33.4e9 B	0.9B smaller than Q3_K_M
Llama-3.3-70B-Instruct.Q4_K_H.gguf	Q4_K_H	37.5e9 B	0.8B smaller than IQ4_XS
ultravox-v0_5-llama-3_3-70b.mmproj.gguf	mmproj	1.38e9 B	multimedia projector
ultravox-v0_6-llama-3_3-70b.mmproj.gguf	mmproj	1.38e9 B	multimedia projector

A discussion thread about the hybrid layer quant approach can be found here on the llama.cpp git repository:

https://github.com/ggml-org/llama.cpp/discussions/13040

steampunque/Llama-3.3-70B-Instruct-Hybrid-GGUF

Mixed Precision GGUF layer quantization of Llama 3.3 70B Instruct by meta-llama

Download the file from below:

steampunque/
Llama-3.3-70B-Instruct-Hybrid-GGUF