Mirrors/llama.cpp

mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-11-01 07:30:17 +01:00

History

Kawrakow 0becb22ac0 IQ4_XS: a 4.25 bpw quantization (#5747 ) * Try IQ4_NL with blocks of 64 - does not look good * iq4_xs: go to super-blocks of 256 and 6-bit scales for blocks of 32 * iq4_xs: CUDA works - 133.2 t/s * iq4_xs: AVX2 dot product * iq4_xs: ARM_NEON dot product * iq4_nl: Metal implementation As usual, Metal / Apple Silicon don't like my quants. * iq3_xs: minor fix * iq4_xs: shrink by using IQ3_S for attn_k and attn_q * iq4_xs: revert using IQ3_S for attn_k and attn_v PPL vs size is good, but CPU performance suffers: on M2 Max TG-128 drops to 21.7 t/s from 28.8, and on a Ryzen-7950X to 14.5 t/s from 15.8 t/s. On CUDA we have 135 t/s when using IQ3_S vs 133 t/s with pure IQ4_XS. * Fix CI * iq4_xs: Added forgotten check for 256 divisibility --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>		2024-02-27 16:34:24 +02:00
..
CMakeLists.txt	build : link against build info instead of compiling against it (#3879 )	2023-11-02 08:50:16 +02:00
quantize.cpp	IQ4_XS: a 4.25 bpw quantization (#5747 )	2024-02-27 16:34:24 +02:00
README.md	readme : add some recent perplexity and bpw measurements to READMES, link for k-quants (#3340 )	2023-09-27 18:30:36 +03:00

README.md

quantize

TODO

Llama 2 7B

Quantization	Bits per Weight (BPW)
Q2_K	3.35
Q3_K_S	3.50
Q3_K_M	3.91
Q3_K_L	4.27
Q4_K_S	4.58
Q4_K_M	4.84
Q5_K_S	5.52
Q5_K_M	5.68
Q6_K	6.56

Llama 2 13B

Quantization	Bits per Weight (BPW)
Q2_K	3.34
Q3_K_S	3.48
Q3_K_M	3.89
Q3_K_L	4.26
Q4_K_S	4.56
Q4_K_M	4.83
Q5_K_S	5.51
Q5_K_M	5.67
Q6_K	6.56

Llama 2 70B

Quantization	Bits per Weight (BPW)
Q2_K	3.40
Q3_K_S	3.47
Q3_K_M	3.85
Q3_K_L	4.19
Q4_K_S	4.53
Q4_K_M	4.80
Q5_K_S	5.50
Q5_K_M	5.65
Q6_K	6.56