File size: 13,797 Bytes
bc32e07 482e5b8 bc32e07 874fab4 e3c5f49 1ae325a 874fab4 50de40a bc32e07 d047f0a 1ae325a d047f0a 4ab18fb d047f0a 726f6c5 d047f0a 874fab4 50de40a 30a0b69 1ae325a d968e06 1ae325a d968e06 1ae325a d968e06 1ae325a d968e06 1ae325a 30a0b69 bc32e07 fa40640 e0bb40e fa40640 6eb7b85 1ae325a 6eb7b85 4ab18fb 6eb7b85 14e974e bc32e07 607ffea bc32e07 482e5b8 30a0b69 482e5b8 30a0b69 874fab4 30a0b69 607ffea 30a0b69 bc32e07 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 |
---
quantized_by: ubergarm
pipeline_tag: text-generation
base_model: zai-org/GLM-4.5-Air
license: mit
base_model_relation: quantized
tags:
- imatrix
- conversational
- ik_llama.cpp
---
## `ik_llama.cpp` imatrix Quantizations of zai-org/GLM-4.5-Air
This quant collection **REQUIRES** [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp/) fork to support the ik's latest SOTA quants and optimizations! Do **not** download these big files and expect them to run on mainline vanilla llama.cpp, ollama, LM Studio, KoboldCpp, etc!
*NOTE* `ik_llama.cpp` can also run your existing GGUFs from bartowski, unsloth, mradermacher, etc if you want to try it out before downloading my quants.
Some of ik's new quants are supported with [Nexesenex/croco.cpp](https://github.com/Nexesenex/croco.cpp) fork of KoboldCPP with Windows builds for CUDA 12.9. Also check for [Windows builds by Thireus here.](https://github.com/Thireus/ik_llama.cpp/releases) which have been CUDA 12.8.
These quants provide best in class perplexity for the given memory footprint.
## Big Thanks
Shout out to Wendell and the **Level1Techs** crew, the community [Forums](https://forum.level1techs.com/t/deepseek-deep-dive-r1-at-home/225826), [YouTube Channel](https://www.youtube.com/@Level1Techs)! **BIG thanks** for providing **BIG hardware** expertise and access to run these experiments and make these great quants available to the community!!!
Also thanks to all the folks in the quanting and inferencing community on [BeaverAI Club Discord](https://huggingface.co/BeaverAI) and on [r/LocalLLaMA](https://www.reddit.com/r/LocalLLaMA/) for tips and tricks helping each other run, test, and benchmark all the fun new models!
## Quant Collection
Perplexity computed against *wiki.test.raw*.

These first two are just test quants for baseline perplexity comparison:
* `BF16` 205.811 GiB (16.004 BPW)
- Final estimate: PPL = 4.5704 +/- 0.02796
* `Q8_0` 109.381 GiB (8.505 BPW)
- Final estimate: PPL = 4.5798 +/- 0.02804
## IQ5_K 77.704 GiB (6.042 BPW)
Final estimate: PPL = 4.5867 +/- 0.02806
<details>
<summary>π Secret Recipe</summary>
```bash
#!/usr/bin/env bash
custom="
# 47 Repeating Layers [0-46]
# Note: All ffn_down.* layers are not divisible by 256 so have limited quantization options.
# Attention
blk\..*\.attn_q.*=q8_0
blk\..*\.attn_k.*=q8_0
blk\..*\.attn_v.*=q8_0
blk\..*\.attn_output.*=q8_0
# First 1 Dense Layers [0]
blk\..*\.ffn_down\.weight=q8_0
blk\..*\.ffn_(gate|up)\.weight=q8_0
# Shared Expert Layers [1-46]
blk\..*\.ffn_down_shexp\.weight=q8_0
blk\..*\.ffn_(gate|up)_shexp\.weight=q8_0
# Routed Experts Layers [1-46]
blk\.(1)\.ffn_down_exps\.weight=q8_0
blk\.(1)\.ffn_(gate|up)_exps\.weight=q8_0
blk\..*\.ffn_down_exps\.weight=q6_0
blk\..*\.ffn_(gate|up)_exps\.weight=iq5_k
# NextN MTP Layer [46]
blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
blk\..*\.nextn\.eh_proj\.weight=q8_0
# Non-Repeating Layers
token_embd\.weight=iq6_k
output\.weight=iq6_k
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N 0 -m 0 \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/imatrix-GLM-4.5-Air-BF16.dat \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-128x9.4B-BF16-00001-of-00005.gguf \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-IQ5_K.gguf \
IQ5_K \
192
```
</details>
## IQ5_KS 72.855 GiB (5.665 BPW)
Final estimate: PPL = 4.5948 +/- 0.02815
<details>
<summary>π Secret Recipe</summary>
```bash
#!/usr/bin/env bash
custom="
# 47 Repeating Layers [0-46]
# Note: All ffn_down.* layers are not divisible by 256 so have limited quantization options.
# Attention
blk\..*\.attn_q.*=iq5_ks
blk\..*\.attn_k.*=q8_0
blk\..*\.attn_v.*=q8_0
blk\..*\.attn_output.*=iq5_ks
# First 1 Dense Layers [0]
blk\..*\.ffn_down\.weight=q6_0
blk\..*\.ffn_(gate|up)\.weight=iq5_ks
# Shared Expert Layers [1-46]
blk\..*\.ffn_down_shexp\.weight=q6_0
blk\..*\.ffn_(gate|up)_shexp\.weight=iq5_ks
# Routed Experts Layers [1-46]
blk\..*\.ffn_down_exps\.weight=q6_0
blk\..*\.ffn_(gate|up)_exps\.weight=iq5_ks
# NextN MTP Layer [46]
blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
blk\..*\.nextn\.eh_proj\.weight=q8_0
# Non-Repeating Layers
token_embd\.weight=iq4_k
output\.weight=iq6_k
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N 0 -m 0 \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/imatrix-GLM-4.5-Air-BF16.dat \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-128x9.4B-BF16-00001-of-00005.gguf \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-IQ5_KS.gguf \
IQ5_KS \
192
```
</details>
## IQ4_K 62.910 GiB (4.892 BPW)
Final estimate: PPL = 4.6273 +/- 0.02839
<details>
<summary>π Secret Recipe</summary>
```bash
#!/usr/bin/env bash
custom="
# 47 Repeating Layers [0-46]
# Note: All ffn_down.* layers are not divisible by 256 so have limited quantization options.
# Attention
blk\..*\.attn_q.*=iq5_ks
blk\..*\.attn_k.*=q8_0
blk\..*\.attn_v.*=q8_0
blk\..*\.attn_output.*=iq5_ks
# First 1 Dense Layers [0]
blk\..*\.ffn_down\.weight=q6_0
blk\..*\.ffn_(gate|up)\.weight=iq5_ks
# Shared Expert Layers [1-46]
blk\..*\.ffn_down_shexp\.weight=q6_0
blk\..*\.ffn_(gate|up)_shexp\.weight=iq5_ks
# Routed Experts Layers [1-46]
blk\..*\.ffn_down_exps\.weight=q5_0
blk\..*\.ffn_(gate|up)_exps\.weight=iq4_k
# NextN MTP Layer [46]
blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
blk\..*\.nextn\.eh_proj\.weight=q8_0
# Non-Repeating Layers
token_embd\.weight=iq4_k
output\.weight=iq6_k
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N 1 -m 1 \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/imatrix-GLM-4.5-Air-BF16.dat \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-128x9.4B-BF16-00001-of-00005.gguf \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-IQ4_K.gguf \
IQ4_K \
192
```
</details>
## IQ4_KSS 54.801 GiB (4.261 BPW)
Final estimate: PPL = 4.7056 +/- 0.02909
<details>
<summary>π Secret Recipe</summary>
```bash
#!/usr/bin/env bash
custom="
# 47 Repeating Layers [0-46]
# Note: All ffn_down.* layers are not divisible by 256 so have limited quantization options.
# Attention
blk\.(0|1)\.attn_q.*=q8_0
blk\.(0|1)\.attn_k.*=q8_0
blk\.(0|1)\.attn_v.*=q8_0
blk\.(0|1)\.attn_output.*=q8_0
blk\..*\.attn_q.*=iq5_ks
blk\..*\.attn_k.*=iq5_ks
blk\..*\.attn_v.*=iq5_ks
blk\..*\.attn_output.*=iq5_ks
# First 1 Dense Layers [0]
blk\..*\.ffn_down\.weight=q6_0
blk\..*\.ffn_(gate|up)\.weight=iq5_ks
# Shared Expert Layers [1-46]
blk\..*\.ffn_down_shexp\.weight=q6_0
blk\..*\.ffn_(gate|up)_shexp\.weight=iq5_ks
# Routed Experts Layers [1-46]
#blk\.(1|46)\.ffn_down_exps\.weight=q8_0
#blk\.(1|46)\.ffn_(gate|up)_exps\.weight=q8_0
blk\..*\.ffn_down_exps\.weight=iq4_nl
blk\..*\.ffn_(gate|up)_exps\.weight=iq4_kss
# NextN MTP Layer [46]
blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
blk\..*\.nextn\.eh_proj\.weight=q8_0
# Non-Repeating Layers
token_embd\.weight=iq4_k
output\.weight=iq6_k
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N 0 -m 0 \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/imatrix-GLM-4.5-Air-BF16.dat \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-128x9.4B-BF16-00001-of-00005.gguf \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-IQ4_KSS.gguf \
IQ4_KSS \
192
```
</details>
## IQ3_KS 49.072 GiB (3.816 BPW)
Final estimate: PPL = 4.7975 +/- 0.02972
<details>
<summary>π Secret Recipe</summary>
```bash
#!/usr/bin/env bash
custom="
# 47 Repeating Layers [0-46]
# Note: All ffn_down.* layers are not divisible by 256 so have limited quantization options.
# Attention
blk\.(0|1)\.attn_q.*=q8_0
blk\.(0|1)\.attn_k.*=q8_0
blk\.(0|1)\.attn_v.*=q8_0
blk\.(0|1)\.attn_output.*=q8_0
blk\..*\.attn_q.*=iq5_ks
blk\..*\.attn_k.*=iq5_ks
blk\..*\.attn_v.*=iq5_ks
blk\..*\.attn_output.*=iq5_ks
# First 1 Dense Layers [0]
blk\..*\.ffn_down\.weight=q6_0
blk\..*\.ffn_(gate|up)\.weight=iq5_ks
# Shared Expert Layers [1-46]
blk\..*\.ffn_down_shexp\.weight=q6_0
blk\..*\.ffn_(gate|up)_shexp\.weight=iq5_ks
# Routed Experts Layers [1-46]
blk\.(1)\.ffn_down_exps\.weight=q6_0
blk\.(1)\.ffn_(gate|up)_exps\.weight=iq5_ks
blk\..*\.ffn_down_exps\.weight=iq4_nl
blk\..*\.ffn_(gate|up)_exps\.weight=iq3_ks
# Non-Repeating Layers
token_embd\.weight=iq4_k
output\.weight=iq6_k
# NextN MTP Layer [46]
blk\..*\.nextn\.embed_tokens\.weight=iq5_ks
blk\..*\.nextn\.shared_head_head\.weight=iq5_ks
blk\..*\.nextn\.eh_proj\.weight=q8_0
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N 0 -m 0 \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/imatrix-GLM-4.5-Air-BF16.dat \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-128x9.4B-BF16-00001-of-00005.gguf \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-PR624-IQ3_KS.gguf \
IQ3_KS \
192
```
</details>
## IQ2_KL 43.870 GiB (3.411 BPW)
Final estimate: PPL = 5.0697 +/- 0.03166
<details>
<summary>π Secret Recipe</summary>
```bash
#!/usr/bin/env bash
custom="
# 47 Repeating Layers [0-46]
# Note: All ffn_down.* layers are not divisible by 256 so have limited quantization options.
# Attention
blk\..*\.attn_q.*=iq4_ks
blk\..*\.attn_k.*=iq5_ks
blk\..*\.attn_v.*=iq5_ks
blk\..*\.attn_output.*=iq4_ks
# First 1 Dense Layers [0]
blk\..*\.ffn_down\.weight=iq4_nl
blk\..*\.ffn_(gate|up)\.weight=iq4_kss
# Shared Expert Layers [1-46]
blk\..*\.ffn_down_shexp\.weight=iq4_nl
blk\..*\.ffn_(gate|up)_shexp\.weight=iq4_kss
# Routed Experts Layers [1-46]
blk\.(1)\.ffn_down_exps\.weight=iq4_nl
blk\.(1)\.ffn_(gate|up)_exps\.weight=iq4_kss
blk\..*\.ffn_down_exps\.weight=iq4_nl
blk\..*\.ffn_(gate|up)_exps\.weight=iq2_kl
# NextN MTP Layer [46]
blk\..*\.nextn\.embed_tokens\.weight=iq4_ks
blk\..*\.nextn\.shared_head_head\.weight=iq4_ks
blk\..*\.nextn\.eh_proj\.weight=q6_0
# Non-Repeating Layers
token_embd\.weight=iq4_k
output\.weight=iq6_k
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N 0 -m 0 \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/imatrix-GLM-4.5-Air-BF16.dat \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-128x9.4B-BF16-00001-of-00005.gguf \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-IQ2_KL.gguf \
IQ2_KL \
192
```
</details>
## IQ1_KT 36.039 GiB (2.802 BPW)
Final estimate: PPL = 5.8214 +/- 0.03767
<details>
<summary>π Secret Recipe</summary>
```bash
#!/usr/bin/env bash
custom="
# 47 Repeating Layers [0-46]
# Note: All ffn_down.* layers are not divisible by 256 so have limited quantization options.
# Attention
blk\..*\.attn_q.*=iq4_kt
blk\..*\.attn_k.*=iq4_kt
blk\..*\.attn_v.*=iq4_kt
blk\..*\.attn_output.*=iq4_kt
# First 1 Dense Layers [0]
blk\..*\.ffn_down\.weight=iq4_nl
blk\..*\.ffn_(gate|up)\.weight=iq4_kt
# Shared Expert Layers [1-46]
blk\..*\.ffn_down_shexp\.weight=iq4_nl
blk\..*\.ffn_(gate|up)_shexp\.weight=iq4_kt
# Routed Experts Layers [1-46]
blk\..*\.ffn_down_exps\.weight=iq4_nl
blk\..*\.ffn_(gate|up)_exps\.weight=iq1_kt
# NextN MTP Layer [46]
blk\..*\.nextn\.embed_tokens\.weight=iq4_kt
blk\..*\.nextn\.shared_head_head\.weight=iq4_kt
blk\..*\.nextn\.eh_proj\.weight=q8_0
# Non-Repeating Layers
token_embd\.weight=iq4_k
output\.weight=iq6_k
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N 1 -m 1 \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/imatrix-GLM-4.5-Air-BF16.dat \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-128x9.4B-BF16-00001-of-00005.gguf \
/mnt/raid/models/ubergarm/GLM-4.5-Air-GGUF/GLM-4.5-Air-IQ1_KT.gguf \
IQ1_KT \
192
```
</details>
## Quick Start
If you want to disable thinking, add `/nothink` (correct, no underscore) at the *end* of your prompt.
```bash
# Clone and checkout
$ git clone https://github.com/ikawrakow/ik_llama.cpp
$ cd ik_llama.cpp
# Build for hybrid CPU+CUDA
$ cmake -B build -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON -DGGML_BLAS=OFF -DGGML_SCHED_MAX_COPIES=1
$ cmake --build build --config Release -j $(nproc)
# Run API server
$ ./build/bin/llama-server \
--model GLM-4.5-Air-IQ4_KSS-00001-of-00002.gguf \
--alias ubergarm/GLM-4.5-Air-IQ4_KSS \
--chat-template chatglm4 \
--ctx-size 32768 \
-fa -fmoe \
-ctk q8_0 -ctv q8_0 \
-ub 4096 -b 4096 \
-ngl 99 \
-ot exps=CPU \
--parallel 1 \
--threads 8 \
--host 127.0.0.1 \
--port 8080 \
--no-mmap
```
## References
* [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp)
* [Getting Started Guide (already out of date lol)](https://github.com/ikawrakow/ik_llama.cpp/discussions/258)
* [ubergarm-imatrix-calibration-corpus-v02.txt](https://gist.github.com/ubergarm/edfeb3ff9c6ec8b49e88cdf627b0711a?permalink_comment_id=5682584#gistcomment-5682584)
* [Mainline llama.cpp Draft PR14939](https://github.com/ggml-org/llama.cpp/pull/14939)
* [ik_llama.cpp GLM-4.5 MoE PR668](https://github.com/ikawrakow/ik_llama.cpp/pull/668)
|