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BAAI Models

5 modelsGeneral models from $0.03/M input

Usage

Last 30 days · 2026-07-22 to 2026-08-20

Tokens

28.6B

Requests

974K

Models in use

5 of 5

Tokens per day, stacked by model

0640M1.3B07-2207-2908-0508-1208-192026-07-22 — 1,053,474,730 tokens BAAI/bge-reranker-v2-m3: 1,053,471,285 BAAI/bge-large-zh-v1.5: 3,385 bge-large-zh: 602026-07-23 — 1,022,854,415 tokens BAAI/bge-reranker-v2-m3: 1,022,851,500 BAAI/bge-large-zh-v1.5: 1,885 bge-large-zh: 885 BAAI/bge-large-en-v1.5: 1452026-07-24 — 990,963,140 tokens BAAI/bge-reranker-v2-m3: 990,954,415 bge-large-zh: 4,465 BAAI/bge-large-zh-v1.5: 4,245 BAAI/bge-large-en-v1.5: 152026-07-25 — 961,907,190 tokens BAAI/bge-reranker-v2-m3: 959,455,760 bge-large-zh: 2,451,200 BAAI/bge-large-en-v1.5: 2302026-07-26 — 778,287,450 tokens BAAI/bge-reranker-v2-m3: 778,287,350 bge-large-zh: 1002026-07-27 — 1,021,572,610 tokens BAAI/bge-reranker-v2-m3: 1,021,542,415 bge-large-zh: 29,635 BAAI/bge-large-zh-v1.5: 5602026-07-28 — 969,886,190 tokens BAAI/bge-reranker-v2-m3: 968,215,680 bge-large-zh: 1,668,215 BAAI/bge-large-zh-v1.5: 2,275 BAAI/bge-large-en-v1.5: 15 bge-large-en: 52026-07-29 — 1,016,377,840 tokens BAAI/bge-reranker-v2-m3: 1,015,136,525 bge-large-zh: 727,180 BAAI/bge-large-en-v1.5: 513,190 BAAI/bge-large-zh-v1.5: 9452026-07-30 — 926,528,575 tokens BAAI/bge-reranker-v2-m3: 926,150,125 BAAI/bge-large-zh-v1.5: 335,185 bge-large-en: 43,235 BAAI/bge-large-en-v1.5: 15 bge-large-zh: 152026-07-31 — 1,200,155,290 tokens BAAI/bge-reranker-v2-m3: 950,644,825 BAAI/bge-large-en-v1.5: 249,444,830 bge-large-en: 43,890 BAAI/bge-large-zh-v1.5: 21,7452026-08-01 — 1,002,474,025 tokens BAAI/bge-reranker-v2-m3: 1,002,303,180 bge-large-en: 162,095 BAAI/bge-large-zh-v1.5: 8,050 bge-large-zh: 465 BAAI/bge-large-en-v1.5: 2352026-08-02 — 818,452,610 tokens BAAI/bge-reranker-v2-m3: 818,097,590 bge-large-en: 273,660 BAAI/bge-large-zh-v1.5: 79,675 bge-large-zh: 1,6852026-08-03 — 901,382,615 tokens BAAI/bge-reranker-v2-m3: 901,339,250 bge-large-en: 27,085 BAAI/bge-large-zh-v1.5: 15,805 bge-large-zh: 4752026-08-04 — 1,119,161,055 tokens BAAI/bge-reranker-v2-m3: 1,119,057,000 bge-large-en: 88,690 BAAI/bge-large-zh-v1.5: 14,800 bge-large-zh: 5652026-08-05 — 1,098,696,445 tokens BAAI/bge-reranker-v2-m3: 1,098,630,770 BAAI/bge-large-zh-v1.5: 43,075 BAAI/bge-large-en-v1.5: 22,6002026-08-06 — 1,077,298,695 tokens BAAI/bge-reranker-v2-m3: 1,077,292,130 BAAI/bge-large-zh-v1.5: 6,285 bge-large-zh: 2802026-08-07 — 1,038,032,735 tokens BAAI/bge-reranker-v2-m3: 1,038,032,685 BAAI/bge-large-zh-v1.5: 35 BAAI/bge-large-en-v1.5: 152026-08-08 — 1,111,690,375 tokens BAAI/bge-reranker-v2-m3: 1,111,689,990 BAAI/bge-large-zh-v1.5: 3852026-08-09 — 1,063,360,220 tokens BAAI/bge-reranker-v2-m3: 1,038,684,470 BAAI/bge-large-en-v1.5: 24,646,760 BAAI/bge-large-zh-v1.5: 28,870 bge-large-zh: 1202026-08-10 — 1,261,013,440 tokens BAAI/bge-reranker-v2-m3: 1,261,013,335 BAAI/bge-large-zh-v1.5: 90 BAAI/bge-large-en-v1.5: 152026-08-11 — 1,117,089,765 tokens BAAI/bge-reranker-v2-m3: 1,114,567,230 bge-large-zh: 2,517,590 BAAI/bge-large-zh-v1.5: 4,9452026-08-12 — 781,810,540 tokens BAAI/bge-reranker-v2-m3: 780,063,905 BAAI/bge-large-zh-v1.5: 1,746,6352026-08-13 — 749,362,230 tokens BAAI/bge-reranker-v2-m3: 749,351,845 BAAI/bge-large-zh-v1.5: 5,975 bge-large-zh: 2,445 BAAI/bge-large-en-v1.5: 1,9652026-08-14 — 623,179,655 tokens BAAI/bge-reranker-v2-m3: 623,173,160 BAAI/bge-large-zh-v1.5: 4,815 bge-large-zh: 1,6802026-08-15 — 584,617,145 tokens BAAI/bge-reranker-v2-m3: 584,616,140 BAAI/bge-large-zh-v1.5: 990 BAAI/bge-large-en-v1.5: 152026-08-16 — 533,563,845 tokens BAAI/bge-reranker-v2-m3: 526,591,140 BAAI/bge-large-zh-v1.5: 6,954,635 bge-large-zh: 17,985 BAAI/bge-large-en-v1.5: 60 bge-large-en: 252026-08-17 — 451,008,250 tokens BAAI/bge-reranker-v2-m3: 450,640,385 BAAI/bge-large-zh-v1.5: 367,850 BAAI/bge-large-en-v1.5: 152026-08-18 — 821,141,530 tokens BAAI/bge-reranker-v2-m3: 821,082,025 BAAI/bge-large-zh-v1.5: 49,480 bge-large-zh: 10,010 BAAI/bge-large-en-v1.5: 152026-08-19 — 1,182,379,165 tokens BAAI/bge-reranker-v2-m3: 1,182,244,805 BAAI/bge-large-en-v1.5: 125,160 BAAI/bge-large-zh-v1.5: 9,2002026-08-20 — 1,279,015,410 tokens BAAI/bge-reranker-v2-m3: 1,274,933,250 BAAI/bge-large-zh-v1.5: 3,922,040 bge-large-zh: 160,120
  • BAAI/bge-reranker-v2-m3
  • BAAI/bge-large-en-v1.5
  • BAAI/bge-large-zh-v1.5
  • bge-large-zh
  • bge-large-en

Which models that traffic went to

  1. BAAI/bge-reranker-v2-m399.0%28.3B
  2. BAAI/bge-large-en-v1.51.0%275M
  3. BAAI/bge-large-zh-v1.5<0.1%13.6M
  4. Bge Large Zh<0.1%7.6M
  5. Bge Large En<0.1%639K

Share of 28.6B tokens.

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 5 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

All 5 BAAI Models

Open in model list
BAAI 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
BAAI/bge-large-en-v1.5Takes text, vision. Output modality not published.$0.03$0.03/M
BAAI/bge-large-zh-v1.5Takes text, vision. Output modality not published.$0.03$0.03/M
BAAI/bge-reranker-v2-m3Takes text, vision. Output modality not published.$0.03$0.03/M
bge-large-enTakes text, vision. Output modality not published.$0.07$0.07/M
bge-large-zhTakes text, vision. Output modality not published.$0.07$0.07/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.

BAAI on AIHubMix

Which BAAI model should I start with?

BAAI/bge-large-en-v1.5 at $0.03/M input — the cheapest entry here that declares tool calling. Move up to bge-large-en when answer quality matters more than cost.

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 (BAAI/…), 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.

Do I need a separate BAAI 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

See all model authors →
Qwen
141 modelsOpenAI
133 modelsGoogle
83 modelsZ.AI
66 modelsLlama
52 models

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