BAAI Models

4 modelsGeneral models from $0.034/M input

Usage

Last 25 days · 2026-08-26 to 2026-09-22

Tokens

43.1M

Requests

36.8K

Models in use

4 of 4

Tokens per day, stacked by model

04.6M9.1M08-2609-0209-0909-162026-08-26 — 142,500 tokens BAAI/bge-large-zh-v1.5: 142,345 BAAI/bge-large-en-v1.5: 135 bge-large-zh: 10 bge-large-en: 102026-08-27 — 106,800 tokens BAAI/bge-large-zh-v1.5: 106,8002026-08-28 — 863,990 tokens BAAI/bge-large-zh-v1.5: 674,280 BAAI/bge-large-en-v1.5: 189,7102026-08-29 — 154,115 tokens BAAI/bge-large-zh-v1.5: 149,830 bge-large-zh: 2,265 BAAI/bge-large-en-v1.5: 2,0202026-08-30 — 848,465 tokens BAAI/bge-large-zh-v1.5: 837,920 BAAI/bge-large-en-v1.5: 10,5452026-08-31 — 604,935 tokens BAAI/bge-large-zh-v1.5: 604,905 BAAI/bge-large-en-v1.5: 302026-09-01 — 340,900 tokens BAAI/bge-large-zh-v1.5: 340,885 BAAI/bge-large-en-v1.5: 152026-09-02 — 634,595 tokens BAAI/bge-large-zh-v1.5: 634,5952026-09-03 — 7,530,235 tokens BAAI/bge-large-zh-v1.5: 7,522,565 BAAI/bge-large-en-v1.5: 6,890 bge-large-zh: 7802026-09-04 — 85,060 tokens BAAI/bge-large-zh-v1.5: 84,985 BAAI/bge-large-en-v1.5: 30 bge-large-en: 25 bge-large-zh: 202026-09-05 — 2,590,785 tokens BAAI/bge-large-zh-v1.5: 2,590,765 BAAI/bge-large-en-v1.5: 202026-09-06 — 4,971,780 tokens BAAI/bge-large-zh-v1.5: 4,971,750 BAAI/bge-large-en-v1.5: 302026-09-07 — 215,835 tokens BAAI/bge-large-zh-v1.5: 201,165 bge-large-zh: 14,6702026-09-08 — 3,845,020 tokens BAAI/bge-large-zh-v1.5: 3,845,005 BAAI/bge-large-en-v1.5: 152026-09-09 — 1,557,525 tokens BAAI/bge-large-zh-v1.5: 1,556,620 bge-large-zh: 9052026-09-10 — 1,578,295 tokens BAAI/bge-large-zh-v1.5: 1,578,265 BAAI/bge-large-en-v1.5: 302026-09-11 — 9,106,675 tokens BAAI/bge-large-zh-v1.5: 9,106,645 BAAI/bge-large-en-v1.5: 302026-09-12 — 1,261,620 tokens BAAI/bge-large-zh-v1.5: 1,261,605 BAAI/bge-large-en-v1.5: 152026-09-13 — 820,330 tokens BAAI/bge-large-zh-v1.5: 820,325 bge-large-zh: 52026-09-14 — 476,130 tokens BAAI/bge-large-zh-v1.5: 476,1302026-09-15 — 2,198,270 tokens BAAI/bge-large-zh-v1.5: 2,198,2702026-09-16 — 1,396,175 tokens BAAI/bge-large-zh-v1.5: 1,396,1752026-09-17 — 1,742,055 tokens bge-large-zh: 1,187,235 bge-large-en: 441,850 BAAI/bge-large-zh-v1.5: 112,9702026-09-18 — 5,110 tokens bge-large-en: 5,1102026-09-22 — 3,240 tokens bge-large-en: 3,240
  • BAAI/bge-large-zh-v1.5
  • bge-large-zh
  • bge-large-en
  • BAAI/bge-large-en-v1.5

Which models that traffic went to

  1. BAAI/bge-large-zh-v1.595.7%41.2M
  2. Bge Large Zh2.8%1.2M
  3. Bge Large En1.0%450K
  4. BAAI/bge-large-en-v1.50.5%210K

Share of 43.1M 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 25 days, counting the 4 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

All 4 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.$0.034$0.034/M
BAAI/bge-large-zh-v1.5Takes text, vision. Output modality not published.$0.034$0.034/M
bge-large-enTakes text, vision. Output modality not published.$0.068$0.068/M
bge-large-zhTakes text, vision. Output modality not published.$0.068$0.068/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 $0.034/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
148 modelsOpenAI
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87 modelsZ.AI
71 modelsLlama
53 models

Start calling BAAI in one line

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