Baidu Models

23 modelsGeneral models from $0.0136/M inputUp to 183K context

Usage

Last 30 days · 2026-10-02 to 2026-10-31

Tokens

170M

Requests

32.6K

Models in use

22 of 23

Tokens per day, stacked by model

024.5M49.1M10-0210-0910-1610-2310-302026-10-02 — 287,785 tokens ernie-5.1: 160,120 ernie-5.0-thinking-preview: 127,6652026-10-03 — 572,220 tokens ernie-5.1: 544,495 qianfan-ocr: 18,615 ernie-5.0: 7,160 ernie-5.0-thinking-preview: 1,850 ernie-4.5-turbo-vl: 1002026-10-04 — 584,025 tokens ernie-5.1: 584,0252026-10-05 — 81,310 tokens ernie-5.1: 80,170 ernie-5.0: 395 ernie-5.0-thinking-preview: 360 ernie-4.5-turbo-vl: 260 qianfan-ocr: 1252026-10-06 — 393,350 tokens ernie-5.1: 295,860 ernie-5.0: 34,955 qianfan-ocr: 31,745 ernie-5.0-thinking-preview: 30,7902026-10-07 — 343,910 tokens ernie-5.1: 299,290 musesteamer-air-image: 20,000 qianfan-ocr: 16,995 ernie-4.5-turbo-vl: 6,380 ernie-5.0: 1,150 ernie-5.0-thinking-preview: 952026-10-08 — 1,811,870 tokens ernie-5.1: 1,589,380 ernie-5.0-thinking-preview: 145,765 qianfan-ocr: 62,020 2 more models: 13,275 ernie-5.0: 1,4302026-10-09 — 6,332,940 tokens ernie-5.1: 6,099,115 2 more models: 74,115 pp-structurev3: 62,500 paddleocr-vl-0.9b: 62,500 qianfan-ocr: 33,340 ernie-5.0: 1,3702026-10-10 — 3,437,700 tokens ernie-5.1: 3,394,295 2 more models: 28,670 qianfan-ocr: 9,300 ernie-5.0: 3,920 ernie-5.0-thinking-preview: 1,5152026-10-11 — 1,130,035 tokens ernie-5.1: 1,107,525 ernie-5.0: 11,410 ernie-4.5-turbo-vl: 10,070 2 more models: 1,0302026-10-12 — 525,010 tokens ernie-5.1: 482,820 qianfan-ocr: 20,220 ernie-4.5-turbo-vl: 20,150 ernie-5.0: 1,785 ernie-5.0-thinking-preview: 30 2 more models: 52026-10-13 — 527,170 tokens ernie-5.1: 384,805 ernie-4.5-turbo-vl: 100,550 qianfan-ocr: 37,655 ernie-5.0: 4,135 ernie-5.0-thinking-preview: 20 2 more models: 52026-10-14 — 1,514,405 tokens ernie-5.1: 1,486,645 2 more models: 26,245 ernie-5.0: 1,5152026-10-15 — 2,013,795 tokens ernie-5.1: 1,786,685 ernie-5.0-thinking-preview: 144,775 qianfan-ocr: 78,390 ernie-5.0: 3,9452026-10-16 — 20,764,760 tokens ernie-5.1: 20,648,440 ernie-4.5-turbo-vl: 67,870 ernie-5.0-thinking-preview: 44,440 ernie-5.0: 4,0102026-10-17 — 2,231,925 tokens ernie-5.1: 2,182,470 qianfan-ocr: 43,365 ernie-5.0: 3,225 ernie-5.0-thinking-preview: 1,935 ernie-4.5-turbo-vl: 9302026-10-18 — 983,410 tokens ernie-5.1: 946,380 qianfan-ocr: 19,280 ernie-5.0-thinking-preview: 8,910 ernie-5.0: 6,770 ernie-4.5-turbo-vl: 2,0702026-10-19 — 9,504,475 tokens ernie-5.1: 8,911,880 paddleocr-vl-0.9b: 375,000 ernie-5.0-thinking-preview: 208,305 ernie-5.0: 7,280 ernie-4.5-turbo-vl: 2,0102026-10-20 — 3,744,575 tokens qianfan-ocr: 3,164,440 ernie-5.1: 396,655 ernie-5.0-thinking-preview: 177,220 ernie-5.0: 4,820 ernie-4.5-turbo-vl: 1,4402026-10-21 — 2,753,000 tokens ernie-5.1: 1,285,325 pp-structurev3: 1,250,000 qianfan-ocr: 180,925 ernie-5.0-thinking-preview: 29,180 ernie-5.0: 5,680 ernie-4.5-turbo-vl: 1,8902026-10-22 — 1,140,620 tokens ernie-5.1: 1,003,400 qianfan-ocr: 119,735 ernie-4.5-turbo-vl: 7,770 ernie-5.0: 5,635 ernie-5.0-thinking-preview: 4,070 2 more models: 102026-10-23 — 1,388,780 tokens ernie-5.1: 972,275 qianfan-ocr: 369,970 ernie-5.0: 38,695 ernie-5.0-thinking-preview: 3,980 ernie-4.5-turbo-vl: 2,460 2 more models: 1,4002026-10-24 — 1,234,225 tokens ernie-5.1: 925,540 ernie-5.0: 251,005 ernie-5.0-thinking-preview: 46,195 qianfan-ocr: 9,325 ernie-4.5-turbo-vl: 2,1602026-10-25 — 476,125 tokens ernie-5.1: 455,955 qianfan-ocr: 9,300 ernie-5.0: 5,265 ernie-5.0-thinking-preview: 3,355 ernie-4.5-turbo-vl: 2,2502026-10-26 — 826,650 tokens ernie-5.1: 663,345 qianfan-ocr: 149,240 ernie-5.0: 7,945 ernie-5.0-thinking-preview: 4,080 ernie-4.5-turbo-vl: 2,0402026-10-27 — 1,706,305 tokens ernie-5.0-thinking-preview: 1,142,050 ernie-5.1: 388,445 qianfan-ocr: 166,670 ernie-5.0: 6,425 ernie-4.5-turbo-vl: 2,7152026-10-28 — 49,063,500 tokens ernie-5.1: 42,328,945 ernie-5.0-thinking-preview: 6,651,825 qianfan-ocr: 74,860 ernie-5.0: 5,720 ernie-4.5-turbo-vl: 2,1502026-10-29 — 11,269,210 tokens ernie-5.1: 10,785,740 qianfan-ocr: 427,390 ernie-5.0: 51,155 ernie-5.0-thinking-preview: 3,215 ernie-4.5-turbo-vl: 1,7102026-10-30 — 28,679,275 tokens ernie-5.1: 28,581,290 qianfan-ocr: 97,9852026-10-31 — 14,340,790 tokens ernie-5.1: 12,769,315 musesteamer-air-image: 1,526,500 qianfan-ocr: 44,975
  • ernie-5.1
  • ernie-5.0-thinking-preview
  • qianfan-ocr
  • musesteamer-air-image
  • pp-structurev3
  • ernie-5.0
  • paddleocr-vl-0.9b
  • ernie-4.5-turbo-vl
  • 2 more models

Which models that traffic went to

  1. ERNIE 5.189.3%152M
  2. ERNIE 5.0 Thinking Preview5.2%8.8M
  3. Qianfan Ocr3.1%5.2M
  4. Musesteamer Air Image0.9%1.5M
  5. Pp Structurev30.8%1.3M
  6. ERNIE 5.00.3%477K
  7. Paddleocr VL 0.9b0.3%438K
  8. ERNIE 4.5 Turbo VL0.1%237K
  9. 2 more models0.1%145K

Share of 170M tokens. 12 models with traffic report no token counts and cannot be ranked here, including ernie-4.5-turbo-latest and ernie-4.5 — 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 23 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

All 23 Baidu Models

Open in model list
Baidu 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
ernie-5.0-thinking-previewTakes text, returns text.183K64K$0.822$3.288/M$0.822/M6 tok/s2.20 s
ernie-4.5Takes text, vision, returns text.160K64K$0.068$0.272/M—99 tok/s0.95 s
ernie-4.5-turbo-vlTakes text, vision, returns text.139K16K$0.4$1.2/M—9 tok/s1.29 s
ernie-4.5-turbo-latestTakes text, vision, returns text.135K12K$0.11$0.44/M—18 tok/s0.62 s
ERNIE-X1.1-PreviewTakes text, returns text.119K64K$0.136$0.544/M—4 tok/s1.26 s
ernie-5.1Takes text, returns text.119K66K$0.5634$2.5353/M$0.5634/M11 tok/s3.76 s
ernie-5.0Takes text, vision, returns text.119K66K$0.8219$3.2877/M$0.8219/M5 tok/s2.29 s
ernie-5.0-thinking-expTakes text, returns text.119K66K$0.8219$3.2877/M$0.8219/M——
ernie-x1-turboTakes text, returns text.51K28K$0.136$0.544/M———
qianfan-ocrTakes text, vision, returns text.32K28K$0.062$0.248/M—20 tok/s0.38 s
qianfan-ocr-fastTakes text, vision, returns text.32K28K$0.664$2.7383/M———
paddleocr-vl-0.9bTakes , returns text.——Free$0.025/M———
pp-structurev3Takes , returns text.——Free$0.025/M———
ernie-4.5-0.3bTakes text, vision, returns text.——$0.0136$0.0544/M———
embedding-v1Takes text. Output modality not published.——$0.068$0.068/M———
tao-8k——$0.068$0.068/M———
ernie-4.5-turbo-128k-previewTakes text, vision, returns text.——$0.108$0.432/M———
ernie-x1.1-previewTakes , returns text.——$0.136$0.544/M—4 tok/s1.26 s
qianfan-qi-vlTakes , returns text.——$0.2$0.6/M———
baidu/ERNIE-4.5-300B-A47BTakes text, vision, returns text.——$0.32$1.28/M———
cc-ernie-4.5-300b-a47bTakes text, vision, returns text.——$0.32$1.28/M———
ernie-image-turboTakes , returns vision.——$2$2/M———
musesteamer-air-imageTakes , returns vision.——$2$2/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

ERNIE-X1.1-Preview vs baidu/ERNIE-4.5-300B-A47BERNIE-X1.1-Preview vs cc-ernie-4.5-300b-a47bERNIE-X1.1-Preview vs ernie-4.5ERNIE-X1.1-Preview vs qwen3.8-max-previewERNIE-X1.1-Preview vs kimi-k3

Baidu on AIHubMix

Which Baidu model should I start with?

ernie-4.5-0.3b at $0.0136/M input — the cheapest entry here that declares tool calling. Move up to ernie-image-turbo when answer quality matters more than cost, or to ernie-5.0-thinking-preview for long-form reasoning.

Which of these models reason before answering?

6 of the 23 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 (baidu/…), 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 Baidu 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
154 modelsOpenAI
144 modelsGoogle
90 modelsZ.AI
72 modelsLlama
53 models

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