Z.AI Models

72 modelsGeneral models free to startUp to 1.05M contextOfficial site ↗

Usage

Last 30 days · 2026-10-06 to 2026-11-04

Tokens

395B

Requests

2.3M

Models in use

70 of 72

Tokens per day, stacked by model

015.9B31.8B10-0610-1310-2010-2711-032026-10-06 — 9,530,492,620 tokens glm-5.3-flash: 5,387,307,380 coding-glm-5.3: 1,255,473,860 coding-glm-5.3-flash: 1,116,090,780 glm-5.3: 948,055,000 35 more models: 489,092,050 coding-glm-5.3-free: 121,525,420 glm-5.2: 108,812,060 glm-5.3-flashx: 80,380,175 coding-glm-5.3-flash-free: 23,755,8952026-10-07 — 19,628,992,655 tokens coding-glm-5.3-flash: 11,859,547,760 glm-5.3-flash: 3,846,335,185 coding-glm-5.3: 1,708,369,245 glm-5.3-flashx: 617,389,325 glm-5.3: 547,792,115 35 more models: 479,708,775 coding-glm-5.3-free: 345,729,735 glm-5.2: 131,246,715 coding-glm-5.3-flash-free: 92,873,8002026-10-08 — 22,778,047,640 tokens coding-glm-5.3-flash: 9,637,685,070 coding-glm-5.3: 5,119,067,290 glm-5.3-flash: 4,319,760,760 glm-5.3: 1,526,409,450 35 more models: 907,568,225 glm-5.3-flashx: 678,825,925 coding-glm-5.3-free: 446,258,920 glm-5.2: 104,328,305 coding-glm-5.3-flash-free: 38,143,6952026-10-09 — 19,144,328,165 tokens coding-glm-5.3: 7,255,573,320 glm-5.3-flash: 5,398,126,545 coding-glm-5.3-flash: 3,596,655,980 glm-5.3-flashx: 1,249,975,110 35 more models: 624,573,105 glm-5.3: 624,558,245 coding-glm-5.3-free: 321,469,230 glm-5.2: 40,998,680 coding-glm-5.3-flash-free: 32,397,9502026-10-10 — 16,238,833,370 tokens coding-glm-5.3: 6,724,279,890 glm-5.3-flash: 4,660,155,060 coding-glm-5.3-flash: 1,754,527,410 glm-5.3-flashx: 1,026,970,900 35 more models: 860,049,100 glm-5.3: 553,385,255 coding-glm-5.3-free: 432,895,430 glm-5.2: 192,769,770 coding-glm-5.3-flash-free: 33,800,5552026-10-11 — 10,083,775,205 tokens coding-glm-5.3: 2,774,759,790 coding-glm-5.3-flash: 2,770,403,875 glm-5.3-flash: 2,673,056,140 35 more models: 901,297,380 coding-glm-5.3-free: 449,906,235 glm-5.3-flashx: 189,480,580 glm-5.3: 149,703,575 glm-5.2: 126,374,685 coding-glm-5.3-flash-free: 48,792,9452026-10-12 — 17,261,401,820 tokens coding-glm-5.3-flash: 5,416,553,860 coding-glm-5.3: 4,298,890,940 glm-5.3-flash: 3,439,773,395 glm-5.3-flashx: 2,402,479,610 35 more models: 793,031,020 coding-glm-5.3-free: 474,151,595 glm-5.3: 270,566,485 glm-5.2: 103,320,140 coding-glm-5.3-flash-free: 62,634,7752026-10-13 — 16,351,843,310 tokens coding-glm-5.3-flash: 4,708,653,500 glm-5.3-flash: 3,640,455,640 glm-5.3-flashx: 3,124,253,840 coding-glm-5.3: 2,406,243,690 glm-5.3: 1,160,415,055 35 more models: 737,502,770 coding-glm-5.3-free: 322,183,445 coding-glm-5.3-flash-free: 168,871,640 glm-5.2: 83,263,7302026-10-14 — 18,531,186,155 tokens coding-glm-5.3-flash: 8,298,993,735 coding-glm-5.3: 4,736,461,360 glm-5.3-flash: 2,973,702,075 glm-5.3-flashx: 954,789,015 35 more models: 515,140,450 glm-5.3: 474,554,585 coding-glm-5.3-flash-free: 294,919,185 coding-glm-5.3-free: 227,485,620 glm-5.2: 55,140,1302026-10-15 — 11,680,969,475 tokens coding-glm-5.3: 3,427,718,885 glm-5.3-flash: 3,315,095,940 coding-glm-5.3-flash: 2,659,100,720 35 more models: 934,488,615 glm-5.3: 543,606,970 glm-5.3-flashx: 348,629,655 coding-glm-5.3-free: 280,759,105 coding-glm-5.3-flash-free: 134,504,795 glm-5.2: 37,064,7902026-10-16 — 17,084,790,830 tokens coding-glm-5.3-flash: 5,255,175,470 glm-5.3-flashx: 3,932,250,000 glm-5.3-flash: 3,338,706,490 coding-glm-5.3: 2,654,108,785 glm-5.3: 1,131,170,790 35 more models: 349,153,830 coding-glm-5.3-free: 308,437,180 coding-glm-5.3-flash-free: 76,970,480 glm-5.2: 38,817,8052026-10-17 — 9,622,314,580 tokens coding-glm-5.3-flash: 2,999,028,495 glm-5.3-flash: 2,605,892,825 coding-glm-5.3: 2,160,124,130 glm-5.3-flashx: 490,289,270 35 more models: 459,835,925 glm-5.3: 434,576,700 coding-glm-5.3-free: 354,099,420 coding-glm-5.3-flash-free: 76,629,265 glm-5.2: 41,838,5502026-10-18 — 9,214,929,190 tokens coding-glm-5.3-flash: 3,989,356,065 glm-5.3-flash: 2,134,631,070 coding-glm-5.3: 1,836,422,995 35 more models: 419,101,665 glm-5.3: 340,211,915 coding-glm-5.3-free: 259,019,975 coding-glm-5.3-flash-free: 103,027,980 glm-5.3-flashx: 81,328,420 glm-5.2: 51,829,1052026-10-19 — 13,042,213,625 tokens coding-glm-5.3-flash: 4,380,475,055 glm-5.3-flash: 3,435,340,225 coding-glm-5.3: 2,350,520,240 glm-5.3: 1,514,793,940 glm-5.2: 411,527,865 35 more models: 342,253,190 glm-5.3-flashx: 271,616,740 coding-glm-5.3-free: 247,733,640 coding-glm-5.3-flash-free: 87,952,7302026-10-20 — 10,077,841,375 tokens coding-glm-5.3: 3,659,018,270 glm-5.3-flash: 3,017,562,815 coding-glm-5.3-flash: 1,439,134,295 glm-5.3: 734,223,685 35 more models: 478,760,995 glm-5.3-flashx: 223,727,560 coding-glm-5.3-free: 210,905,170 glm-5.2: 203,893,615 coding-glm-5.3-flash-free: 110,614,9702026-10-21 — 11,666,597,120 tokens coding-glm-5.3: 3,793,142,885 glm-5.3-flash: 3,013,805,120 glm-5.3: 1,826,027,190 coding-glm-5.3-flash: 1,608,170,165 35 more models: 514,162,825 glm-5.3-flashx: 327,578,445 coding-glm-5.3-free: 304,704,805 glm-5.2: 154,061,980 coding-glm-5.3-flash-free: 124,943,7052026-10-22 — 11,093,558,335 tokens glm-5.3-flash: 3,749,760,565 coding-glm-5.3-flash: 3,036,060,860 coding-glm-5.3: 2,489,386,855 glm-5.3: 584,363,575 35 more models: 488,772,180 glm-5.3-flashx: 342,851,540 coding-glm-5.3-free: 209,946,050 coding-glm-5.3-flash-free: 111,047,180 glm-5.2: 81,369,5302026-10-23 — 10,290,634,850 tokens coding-glm-5.3-flash: 3,509,481,875 coding-glm-5.3: 2,501,623,190 glm-5.3-flash: 1,900,325,190 glm-5.3: 873,521,960 35 more models: 745,498,910 coding-glm-5.3-free: 288,787,745 coding-glm-5.3-flash-free: 210,741,795 glm-5.3-flashx: 193,664,980 glm-5.2: 66,989,2052026-10-24 — 6,971,341,090 tokens coding-glm-5.3: 2,861,898,160 coding-glm-5.3-flash: 1,645,169,870 glm-5.3-flash: 860,851,040 35 more models: 809,231,115 coding-glm-5.3-free: 268,817,345 coding-glm-5.3-flash-free: 264,015,595 glm-5.3-flashx: 119,140,640 glm-5.3: 75,381,390 glm-5.2: 66,835,9352026-10-25 — 8,196,085,300 tokens coding-glm-5.3-flash: 2,376,536,615 glm-5.3-flash: 2,163,033,555 coding-glm-5.3: 2,063,271,185 35 more models: 488,738,605 coding-glm-5.3-flash-free: 441,102,650 coding-glm-5.3-free: 332,583,430 glm-5.3-flashx: 173,547,485 glm-5.2: 102,607,545 glm-5.3: 54,664,2302026-10-26 — 8,420,726,575 tokens coding-glm-5.3: 2,190,950,065 glm-5.3-flash: 1,610,709,100 coding-glm-5.3-flash: 1,564,434,550 glm-5.3: 1,326,967,785 35 more models: 1,018,325,420 coding-glm-5.3-free: 261,667,850 coding-glm-5.3-flash-free: 207,978,720 glm-5.3-flashx: 156,682,640 glm-5.2: 83,010,4452026-10-27 — 9,636,216,290 tokens coding-glm-5.3: 2,503,293,920 glm-5.3-flash: 1,950,761,235 coding-glm-5.3-flash: 1,931,086,045 glm-5.3: 1,575,785,410 35 more models: 624,319,095 coding-glm-5.3-free: 379,846,115 glm-5.3-flashx: 273,464,420 coding-glm-5.3-flash-free: 205,364,910 glm-5.2: 192,295,1402026-10-28 — 11,813,599,990 tokens coding-glm-5.3-flash: 3,183,495,935 coding-glm-5.3: 2,584,541,555 glm-5.3: 2,239,216,560 glm-5.3-flash: 1,581,061,685 glm-5.3-flashx: 859,835,730 35 more models: 715,906,690 coding-glm-5.3-free: 355,881,400 coding-glm-5.3-flash-free: 218,077,770 glm-5.2: 75,582,6652026-10-29 — 14,814,073,605 tokens glm-5.3-flash: 3,862,996,225 glm-5.3-flashx: 3,519,629,585 coding-glm-5.3: 2,660,036,085 coding-glm-5.3-flash: 2,519,216,035 glm-5.3: 1,058,851,720 35 more models: 596,752,380 coding-glm-5.3-free: 294,450,815 coding-glm-5.3-flash-free: 205,073,850 glm-5.2: 97,066,9102026-10-30 — 31,801,743,370 tokens glm-5.3: 19,252,284,815 coding-glm-5.3-flash: 4,767,751,450 coding-glm-5.3: 3,814,282,060 glm-5.3-flash: 1,974,925,405 35 more models: 686,924,610 glm-5.3-flashx: 427,834,595 coding-glm-5.3-free: 346,159,850 glm-5.2: 343,887,000 coding-glm-5.3-flash-free: 187,693,5852026-10-31 — 9,428,681,470 tokens coding-glm-5.3: 3,680,796,100 coding-glm-5.3-flash: 2,082,635,275 glm-5.3: 1,375,971,915 glm-5.3-flash: 809,454,335 35 more models: 510,121,530 glm-5.2: 443,199,935 coding-glm-5.3-free: 261,987,860 glm-5.3-flashx: 150,736,450 coding-glm-5.3-flash-free: 113,778,0702026-11-01 — 9,956,069,750 tokens glm-5.3: 4,985,167,695 coding-glm-5.3: 2,097,308,505 glm-5.3-flash: 1,026,735,670 35 more models: 634,877,540 coding-glm-5.3-flash: 364,847,770 glm-5.2: 361,730,125 coding-glm-5.3-free: 294,059,850 coding-glm-5.3-flash-free: 133,893,225 glm-5.3-flashx: 57,449,3702026-11-02 — 13,944,480,095 tokens glm-5.3-flash: 8,187,285,935 coding-glm-5.3: 2,382,366,420 35 more models: 882,304,495 glm-5.3: 735,139,420 coding-glm-5.3-flash: 733,499,285 coding-glm-5.3-free: 330,723,160 glm-5.3-flashx: 262,157,390 glm-5.2: 261,320,680 coding-glm-5.3-flash-free: 169,683,3102026-11-03 — 8,074,305,855 tokens coding-glm-5.3: 2,275,405,135 coding-glm-5.3-flash: 1,948,390,035 glm-5.3-flash: 1,254,463,720 glm-5.3: 879,944,350 35 more models: 632,445,795 coding-glm-5.3-free: 337,969,210 glm-5.3-flashx: 300,695,745 glm-5.2: 243,805,000 coding-glm-5.3-flash-free: 201,186,8652026-11-04 — 8,828,349,590 tokens coding-glm-5.3: 3,462,764,320 glm-5.3-flash: 1,962,817,440 coding-glm-5.3-flash: 1,200,435,675 35 more models: 794,396,815 glm-5.3: 626,426,085 coding-glm-5.3-free: 333,797,225 glm-5.3-flashx: 245,542,595 coding-glm-5.3-flash-free: 173,140,125 glm-5.2: 29,029,310
  • coding-glm-5.3-flash
  • coding-glm-5.3
  • glm-5.3-flash
  • glm-5.3
  • glm-5.3-flashx
  • coding-glm-5.3-free
  • coding-glm-5.3-flash-free
  • glm-5.2
  • 35 more models

Which models that traffic went to

  1. Coding GLM 5.3 Flash25.9%102B
  2. Coding GLM 5.323.7%93.7B
  3. GLM 5.3 Flash22.8%90.1B
  4. GLM 5.312.3%48.4B
  5. GLM 5.3 Flashx5.8%23.1B
  6. Coding GLM 5.3 (free)2.4%9.4B
  7. Coding GLM 5.3 Flash (free)1.1%4.4B
  8. GLM 5.21.1%4.3B
  9. 35 more models4.9%19.4B

Share of 395B tokens. 27 models with traffic report no token counts and cannot be ranked here, including coding-glm-5-turbo-free and alicloud-glm-4.7 — they are in the request view.

The two views disagree on purpose: a model can take a large share of the calls and a small share of the tokens — many short requests — or the reverse. Which one matters depends on whether your cost is driven by call volume or by prompt length. Measured on AIHubMix over the last 30 days, counting the 72 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

All 72 Z.AI Models

Open in model list
Z.AI models on AIHubMix with input and output modalities, context length, maximum output, price per million tokens including cache read and cache write rates, and measured throughput and latency.
Modalities
coding-glm-5.3-freeTakes text, returns text.1.05M131KFreeFree/M—207 tok/s5.53 s
ox-alphaTakes text, vision, video, returns text.1.05M131KFreeFree/M———
coding-glm-5.3Takes text, returns text.1.05M131K$0.06$0.22/M$0.015/M41 tok/s4.60 s
glm-5.3-flashTakes text, vision, video, returns text.1.05M131K$0.1127$0.3944/M$0.0324/M51 tok/s0.52 s
glm-5.3Takes text, returns text.1.05M131K$1.1268$3.9438/M$0.2817/M32 tok/s0.57 s
glm-5.3-primeTakes text, returns text.1.05M131K$2.35$8.23/M$0.59/M82 tok/s3.62 s
coding-glm-5.2-freeTakes text, returns text.1M131KFreeFree/M—42 tok/s5.90 s
coding-glm-5.3-flash-freeTakes text, vision, video, returns text.1M131KFreeFree/M—35 tok/s4.18 s
coding-glm-5.3-flashTakes text, vision, video, returns text.1M131K$0.0282$0.0986/M$0.007/M31 tok/s4.25 s
coding-glm-5.2Takes text, returns text.1M131K$0.06$0.22/M—41 tok/s3.81 s
glm-5.3-flashxTakes text, vision, video, returns text.1M—$0.282$0.987/M$0.0804/M477 tok/s3.56 s
glm-5.2Takes text, returns text.1M131K$1.1268$3.9438/M$0.2817/M31 tok/s0.88 s
cloudflare-glm-5.2Takes text, returns text.1M131K$1.4$4.4002/M$0.2604/M——
glm-5.2-fast-previewTakes text, returns text.1M131K$2.254$7.889/M$0.5635/M38 tok/s2.00 s
coding-glm-5-turbo-freeTakes text, returns text.205K131KFreeFree/M———
cc-glm-5-turboTakes text, returns text.205K131K$0.06$0.22/M—30 tok/s1.42 s
coding-glm-5-turboTakes text, returns text.205K131K$0.06$0.22/M———
glm-5-turboTakes text, returns text.205K131K$1.2$3.9996/M$0.24/M26 tok/s3.53 s
zai-glm-5-turboTakes text, returns text.205K131K$1.2$3.9996/M$0.24/M26 tok/s3.53 s
coding-glm-4.6-freeTakes text, returns text.200K131KFreeFree/M—35 tok/s3.24 s
coding-glm-4.7-freeTakes text, returns text.200K131KFreeFree/M—37 tok/s4.18 s
coding-glm-5-freeTakes text, returns text.200K131KFreeFree/M—39 tok/s5.13 s
coding-glm-5.1-freeTakes text, returns text.200K131KFreeFree/M—46 tok/s4.17 s
glm-4.6Takes text, returns text.200K131KFreeFree/MFree/M20 tok/s4.40 s
glm-4.7-flash-freeTakes text, returns text.200K131KFreeFree/M—39 tok/s13.04 s
cc-glm-5Takes text, returns text.200K131K$0.06$0.22/M—20 tok/s5.40 s
cc-glm-5.1Takes text, returns text.200K131K$0.06$0.22/M———
coding-glm-4.6Takes text, returns text.200K131K$0.06$0.22/M$0.011/M37 tok/s5.02 s
coding-glm-4.7Takes text, returns text.200K131K$0.06$0.22/M$0.011/M15 tok/s1.33 s
coding-glm-5Takes text, returns text.200K131K$0.06$0.22/M—18 tok/s1.54 s
coding-glm-5.1Takes text, returns text.200K131K$0.06$0.22/M—31 tok/s8.37 s
glm-4.7Takes text, returns text.200K131K$0.274$1.0959/M$0.0548/M36 tok/s5.95 s
glm-5v-turboTakes text, vision, video, returns text.200K131K$0.7042$3.0985/M$0.169/M43 tok/s1.95 s
glm-5.1Takes text, returns text.200K131K$0.845$3.38/M$0.1831/M26 tok/s0.94 s
coding-glm-4.5-airTakes text, returns text.131K—$0.014$0.084/M—14 tok/s1.66 s
glm-4.6vTakes text, vision, video, returns text.131K33K$0.137$0.411/M$0.0274/M——
glm-4.5-airTakes text, returns text.131K98K$0.14$0.84/M—91 tok/s1.42 s
glm-4.5Takes text, returns text.131K98K$0.4$1.6/M—107 tok/s0.46 s
glm-4.5vTakes text, vision, video, returns text.66K16K$0.274$0.822/M—81 tok/s8.45 s
glm-ocrTakes vision, returns text.32K—$0.0282$0.0282/M———
embedding-2Takes text. Output modality not published.8K—$0.0686$0.0686/M———
embedding-3Takes text. Output modality not published.8K—$0.0686$0.0686/M———
glm-imageTakes text, returns vision.——FreeFree/M———
Pro/THUDM/GLM-4.1V-9B-ThinkingTakes , returns text.——$0.04$0.16/M———
THUDM/GLM-4-9B-0414Takes , returns text.——$0.05$0.05/M———
THUDM/GLM-Z1-9B-0414Takes , returns text.——$0.05$0.05/M———
cc-glm-4.6Takes , returns text.——$0.06$0.22/M—62 tok/s8.61 s
cc-glm-4.7Takes , returns text.——$0.06$0.22/M—2 tok/s1.48 s
THUDM/GLM-4-32B-0414Takes , returns text.——$0.08$0.08/M———
THUDM/GLM-Z1-32B-0414Takes , returns text.——$0.08$0.08/M———
glm-4-flashTakes , returns text.——$0.1$0.1/M———
THUDM/GLM-4.1V-9B-ThinkingTakes , returns text.——$0.1$0.1/M———
doubao-1-5-pro-32k-250115Takes , returns text.——$0.108$0.27/M———
chatglm_liteTakes , returns text.——$0.2858$0.2858/M———
alicloud-glm-4.7Takes , returns text.——$0.411$1.9178/M$0.411/M44 tok/s1.01 s
alicloud-glm-5Takes , returns text.——$0.5634$2.5353/M$0.1127/M30 tok/s29.91 s
doubao-1-5-pro-256k-250115Takes , returns text.——$0.684$1.2312/M———
glm-3-turboTakes , returns text.——$0.71$0.71/M———
chatglm_stdTakes , returns text.——$0.7144$0.7144/M———
chatglm_turboTakes , returns text.——$0.7144$0.7144/M———
glm-4.5-airxTakes text, returns text.——$1.1$4.51/M$0.22/M40 tok/s0.62 s
chatglm_proTakes , returns text.——$1.4286$1.4286/M———
glm-4v-plusTakes , returns text.——$2$2/M———
glm-zero-previewTakes , returns text.——$2$2/M—76 tok/s2.11 s
glm-4.5-xTakes text, returns text.——$2.2$8.91/M$0.44/M4 tok/s4.08 s
cbs-glm-4.7Takes , returns text.——$2.25$2.75/M———
glm-4-plusTakes , returns text.——$8$8/M—2 tok/s0.85 s
cogview-3-plusTakes , returns vision.——$10$10/M———
glm-4Takes , returns text.——$14.2$14.2/M———
glm-4vTakes , returns text.——$14.2$14.2/M———
code-davinci-edit-001Takes , returns text.——$20$20/M———
cogview-3Takes , returns vision.——$35.5$35.5/M———

Prices are USD per million tokens; cache read and cache write are the rates for prompt-cache hits and for writing a prompt into the cache. Throughput and latency are measured on AIHubMix — the same figures the model detail page shows — not vendor claims. A dash means the catalog does not publish that field for that model, which is not the same as the model not supporting it.

Common Comparisons

THUDM/GLM-4-32B-0414 vs THUDM/GLM-4-9B-0414THUDM/GLM-4-32B-0414 vs THUDM/GLM-4.1V-9B-ThinkingTHUDM/GLM-4-32B-0414 vs THUDM/GLM-Z1-32B-0414THUDM/GLM-4-32B-0414 vs qwen3.8-max-previewTHUDM/GLM-4-32B-0414 vs kimi-k3

Z.AI on AIHubMix

Which Z.AI model should I start with?

coding-glm-4.6-free is free on input — the cheapest entry here that declares tool calling, and it carries a 200K context. Move up to cogview-3 when answer quality matters more than cost, or to coding-glm-5.3-free for long-form reasoning.

Which of these models reason before answering?

29 of the 72 models here declare a reasoning phase — they work through the problem before producing an answer, which helps on multi-step problems at the cost of extra output tokens. Use the Reasoning filter above the table to see them. The catalog does not record anything further about how they differ, so this page does not sort them into families.

Why are there several entries for the same model?

Because each row is a route you can call, not a model release. Some IDs name an upstream (azure-, alicloud-, cc-), some are the open-weight repository form (THUDM/…), and some differ only in capitalisation, kept so older integrations keep working.

The catalog does not carry a field saying which of those a given row is, so this page does not sort them into buckets it would have to invent. Every row shows that route’s own price, context and speed — compare those directly, and open a model to see the upstreams that serve it.

How is cached input billed?

The Cache read column is the rate for input tokens served from the prompt cache — for example coding-glm-4.6 bills cache hits at 18.33% of the input rate and coding-glm-4.7 bills cache hits at 18.33% of the input rate. Cache write is the surcharge for putting a prompt into the cache in the first place, and only a few upstreams bill it separately. A dash in either column means the catalog carries no cache rate for that model, so plan on paying the full input rate.

Do I need a separate Z.AI account?

No. One AIHubMix key covers every model on this page, and switching between them is a change to the model string — billing, rate limits, and logs stay in one place.

Other Model Authors

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154 modelsOpenAI
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90 modelsLlama
53 modelsByteDance
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