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Jina AI Models

13 modelsGeneral models from $0.05/M inputUp to 1M context

Usage

Last 29 days · 2026-08-10 to 2026-09-07

Tokens

7.4B

Requests

1.7M

Models in use

13 of 13

Tokens per day, stacked by model

0311M621M08-1008-1708-2408-3109-072026-08-10 — 305,869,235 tokens jina-reranker-m0: 136,176,795 jina-embeddings-v4: 61,731,875 jina-embeddings-v3: 52,516,130 5 more models: 39,806,985 jina-reranker-v3: 14,822,105 jina-embeddings-v5-text-nano: 541,805 jina-embeddings-v5-text-small: 123,590 jina-reranker-v3.5: 114,120 jina-deepsearch-v1: 35,8302026-08-11 — 334,143,075 tokens jina-reranker-m0: 157,346,305 jina-embeddings-v4: 73,670,590 jina-embeddings-v3: 53,618,555 jina-deepsearch-v1: 38,048,665 jina-reranker-v3: 10,881,325 jina-embeddings-v5-text-small: 325,850 5 more models: 251,7852026-08-12 — 229,011,720 tokens jina-reranker-m0: 123,469,420 jina-embeddings-v3: 47,522,615 jina-deepsearch-v1: 32,857,020 jina-embeddings-v4: 18,811,790 jina-reranker-v3: 5,890,265 jina-embeddings-v5-text-small: 440,650 5 more models: 17,930 jina-embeddings-v5-text-nano: 2,0302026-08-13 — 260,007,455 tokens jina-reranker-m0: 118,624,510 jina-deepsearch-v1: 83,543,625 jina-embeddings-v3: 53,406,970 jina-reranker-v3: 2,317,490 5 more models: 1,319,430 jina-embeddings-v4: 763,985 jina-embeddings-v5-text-small: 31,4452026-08-14 — 324,764,345 tokens jina-reranker-m0: 101,797,785 jina-deepsearch-v1: 93,754,925 jina-embeddings-v3: 52,879,700 jina-embeddings-v4: 43,362,130 jina-embeddings-v5-text-small: 19,555,520 jina-reranker-v3: 7,900,675 5 more models: 3,372,525 jina-reranker-v3.5: 2,141,0852026-08-15 — 311,180,650 tokens jina-deepsearch-v1: 183,322,230 jina-embeddings-v3: 55,732,195 jina-reranker-m0: 53,936,425 jina-embeddings-v4: 14,999,875 jina-reranker-v3: 1,686,220 jina-reranker-v3.5: 1,378,640 jina-embeddings-v5-text-small: 71,065 5 more models: 53,980 jina-embeddings-v5-text-nano: 202026-08-16 — 24,827,145 tokens jina-deepsearch-v1: 13,426,120 jina-embeddings-v3: 6,820,645 jina-reranker-m0: 3,763,015 jina-embeddings-v5-text-small: 591,075 jina-embeddings-v4: 196,755 jina-reranker-v3.5: 29,5352026-08-17 — 0 tokens2026-08-18 — 77,522,010 tokens jina-reranker-m0: 48,004,780 jina-embeddings-v3: 15,163,025 jina-embeddings-v5-text-small: 8,298,130 jina-embeddings-v4: 3,242,995 jina-reranker-v3: 2,582,440 jina-deepsearch-v1: 152,210 5 more models: 60,660 jina-reranker-v3.5: 17,7702026-08-19 — 270,871,195 tokens jina-reranker-m0: 113,477,360 jina-embeddings-v3: 51,578,265 jina-embeddings-v4: 40,883,755 jina-embeddings-v5-text-small: 33,813,420 jina-reranker-v3.5: 24,527,270 jina-reranker-v3: 4,257,430 jina-deepsearch-v1: 2,333,6952026-08-20 — 257,706,670 tokens jina-reranker-m0: 106,739,040 jina-embeddings-v3: 68,401,105 jina-reranker-v3.5: 38,224,625 jina-embeddings-v5-text-small: 34,616,915 jina-reranker-v3: 8,231,190 jina-embeddings-v4: 1,475,190 jina-deepsearch-v1: 18,6052026-08-21 — 230,166,385 tokens jina-reranker-m0: 100,123,555 jina-embeddings-v3: 90,187,040 jina-embeddings-v5-text-small: 24,660,750 jina-reranker-v3.5: 9,817,995 jina-reranker-v3: 4,779,160 jina-embeddings-v4: 580,145 jina-deepsearch-v1: 17,7402026-08-22 — 133,875,975 tokens jina-embeddings-v3: 48,450,540 jina-reranker-m0: 47,775,240 jina-embeddings-v5-text-small: 27,715,155 jina-reranker-v3.5: 6,090,735 jina-reranker-v3: 2,644,215 5 more models: 606,710 jina-embeddings-v4: 574,145 jina-deepsearch-v1: 19,2352026-08-23 — 193,335,800 tokens jina-embeddings-v4: 62,021,190 jina-embeddings-v3: 49,083,845 jina-reranker-m0: 32,429,070 jina-embeddings-v5-text-small: 29,798,635 jina-reranker-v3.5: 9,374,120 jina-deepsearch-v1: 9,093,210 jina-reranker-v3: 1,523,135 5 more models: 12,5952026-08-24 — 237,212,415 tokens jina-reranker-m0: 109,138,850 jina-embeddings-v3: 59,729,215 jina-embeddings-v5-text-small: 25,543,895 jina-reranker-v3: 16,813,075 jina-embeddings-v4: 14,271,270 jina-reranker-v3.5: 6,521,200 jina-deepsearch-v1: 5,062,260 jina-embeddings-v5-text-nano: 73,300 5 more models: 59,3502026-08-25 — 320,373,185 tokens jina-reranker-m0: 126,901,585 jina-embeddings-v3: 48,512,355 jina-embeddings-v4: 47,063,425 jina-reranker-v3.5: 42,767,860 jina-embeddings-v5-text-small: 34,644,860 jina-reranker-v3: 15,610,530 jina-deepsearch-v1: 4,844,075 5 more models: 20,715 jina-embeddings-v5-text-nano: 7,7802026-08-26 — 216,426,430 tokens jina-reranker-m0: 96,449,240 jina-embeddings-v3: 59,077,000 jina-embeddings-v5-text-small: 23,987,485 jina-reranker-v3.5: 22,502,425 jina-embeddings-v4: 8,946,650 jina-reranker-v3: 5,405,025 jina-deepsearch-v1: 36,165 5 more models: 22,360 jina-embeddings-v5-text-nano: 802026-08-27 — 248,536,305 tokens jina-reranker-m0: 110,445,650 jina-embeddings-v4: 58,176,720 jina-embeddings-v3: 50,149,515 jina-embeddings-v5-text-small: 23,238,840 jina-reranker-v3: 3,398,350 jina-embeddings-v5-text-nano: 2,176,885 jina-reranker-v3.5: 707,295 5 more models: 207,265 jina-deepsearch-v1: 35,7852026-08-28 — 310,787,070 tokens jina-reranker-m0: 113,050,455 jina-embeddings-v4: 94,874,155 jina-embeddings-v3: 52,241,830 jina-embeddings-v5-text-small: 27,523,770 jina-deepsearch-v1: 16,047,220 jina-reranker-v3: 5,104,055 jina-reranker-v3.5: 1,829,200 5 more models: 81,455 jina-embeddings-v5-text-nano: 34,9302026-08-29 — 177,786,280 tokens jina-embeddings-v5-text-small: 71,571,405 jina-reranker-m0: 51,182,650 jina-embeddings-v3: 49,557,260 jina-reranker-v3: 3,662,790 jina-embeddings-v5-text-nano: 1,336,395 jina-embeddings-v4: 386,165 5 more models: 71,355 jina-deepsearch-v1: 18,2602026-08-30 — 157,577,910 tokens jina-embeddings-v3: 56,155,680 jina-embeddings-v5-text-small: 48,802,070 jina-reranker-m0: 38,206,440 jina-reranker-v3.5: 9,479,325 jina-reranker-v3: 4,696,120 jina-embeddings-v4: 202,185 jina-deepsearch-v1: 36,0902026-08-31 — 302,132,090 tokens jina-reranker-m0: 117,245,970 jina-embeddings-v3: 67,230,550 jina-embeddings-v5-text-small: 65,675,475 jina-reranker-v3.5: 20,147,765 jina-embeddings-v4: 19,140,470 jina-embeddings-v5-text-nano: 5,309,280 jina-reranker-v3: 4,775,565 jina-deepsearch-v1: 2,562,460 5 more models: 44,5552026-09-01 — 581,631,520 tokens jina-embeddings-v5-text-nano: 326,323,305 jina-reranker-m0: 123,700,020 jina-embeddings-v3: 53,879,210 jina-embeddings-v5-text-small: 45,772,035 jina-reranker-v3.5: 17,795,245 jina-reranker-v3: 7,773,215 jina-embeddings-v4: 6,148,045 jina-deepsearch-v1: 194,085 5 more models: 46,3602026-09-02 — 621,230,695 tokens jina-reranker-v3.5: 318,170,825 jina-reranker-m0: 119,255,450 jina-embeddings-v5-text-small: 92,883,435 jina-embeddings-v3: 73,141,035 jina-embeddings-v4: 9,659,520 jina-reranker-v3: 5,233,940 jina-deepsearch-v1: 2,448,880 5 more models: 437,6102026-09-03 — 389,892,220 tokens jina-reranker-m0: 117,097,245 jina-embeddings-v4: 96,616,590 jina-embeddings-v5-text-small: 70,110,430 jina-embeddings-v3: 55,079,130 jina-reranker-v3.5: 46,008,695 jina-deepsearch-v1: 3,000,575 jina-reranker-v3: 1,947,080 5 more models: 32,4752026-09-04 — 268,066,865 tokens jina-reranker-m0: 106,992,845 jina-embeddings-v3: 55,957,075 jina-embeddings-v4: 46,796,490 jina-embeddings-v5-text-small: 26,905,395 jina-reranker-v3.5: 26,814,340 jina-reranker-v3: 2,837,910 jina-deepsearch-v1: 1,336,685 5 more models: 426,085 jina-embeddings-v5-text-nano: 402026-09-05 — 175,256,485 tokens jina-reranker-m0: 62,550,370 jina-embeddings-v3: 50,611,205 jina-embeddings-v4: 28,439,940 jina-embeddings-v5-text-small: 24,887,485 jina-reranker-v3: 4,972,075 jina-reranker-v3.5: 2,899,435 jina-embeddings-v5-text-nano: 758,345 5 more models: 84,180 jina-deepsearch-v1: 53,4502026-09-06 — 128,064,780 tokens jina-embeddings-v3: 44,518,735 jina-reranker-m0: 42,380,290 jina-embeddings-v5-text-small: 25,940,360 jina-embeddings-v4: 11,213,330 jina-reranker-v3: 2,137,650 jina-embeddings-v5-text-nano: 1,418,965 jina-reranker-v3.5: 305,635 5 more models: 131,955 jina-deepsearch-v1: 17,8602026-09-07 — 314,258,925 tokens jina-reranker-m0: 119,085,650 jina-reranker-v3.5: 80,215,245 jina-embeddings-v3: 44,427,845 jina-embeddings-v4: 35,047,085 jina-embeddings-v5-text-small: 26,733,625 jina-reranker-v3: 6,919,295 jina-embeddings-v5-text-nano: 1,739,980 5 more models: 71,980 jina-deepsearch-v1: 18,220
  • jina-reranker-m0
  • jina-embeddings-v3
  • jina-embeddings-v5-text-small
  • jina-embeddings-v4
  • jina-reranker-v3.5
  • jina-deepsearch-v1
  • jina-embeddings-v5-text-nano
  • jina-reranker-v3
  • 5 more models

Which models that traffic went to

  1. Jina Reranker M035.1%2.6B
  2. Jina Embeddings V319.8%1.5B
  3. Jina Embeddings V5 Text Small11.0%814M
  4. Jina Embeddings V410.8%799M
  5. Jina Reranker V3.59.3%688M
  6. Jina Deepsearch V16.7%492M
  7. Jina Embeddings V5 Text Nano4.6%340M
  8. Jina Reranker V32.1%159M
  9. 5 more models0.6%47.2M

Share of 7.4B 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 29 days, counting the 13 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

All 13 Jina AI Models

Open in model list
Jina 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
jina-deepsearch-v1Takes text, vision, returns text.1M$0.05$0.05/M44 tok/s1.02 s
jina-reranker-v3Takes text, vision. Output modality not published.131K$0.05$0.05/M53 tok/s0.13 s
jina-reranker-v3.5Takes text, vision. Output modality not published.131K$0.05$0.05/M53 tok/s0.13 s
jina-clip-v2Takes text, vision. Output modality not published.8K$0.05$0.05/M——
jina-colbert-v2Takes text. Output modality not published.8K$0.05$0.05/M——
jina-embeddings-v2-base-codeTakes text. Output modality not published.8K$0.05$0.05/M——
jina-embeddings-v3Takes text. Output modality not published.8K$0.05$0.05/M——
jina-embeddings-v4Takes text, vision. Output modality not published.—$0.05$0.05/M52 tok/s0.60 s
jina-embeddings-v5-text-nanoTakes text, vision. Output modality not published.—$0.05$0.05/M——
jina-embeddings-v5-text-smallTakes text, vision. Output modality not published.—$0.05$0.05/M——
jina-reader—$0.05$0.05/M——
jina-reranker-m0Takes text, vision. Output modality not published.—$0.05$0.05/M——
jina-search—$0.05$0.05/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.

Jina AI on AIHubMix

Which Jina AI model should I start with?

jina-clip-v2 at $0.05/M input — the cheapest entry here that declares a token price, and it carries a 8K context. Move up to jina-deepsearch-v1 when answer quality matters more than cost.

Which of these models reason before answering?

1 of the 13 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-), 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 Jina 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

See all model authors →
Qwen
144 modelsOpenAI
134 modelsGoogle
85 modelsZ.AI
71 modelsLlama
53 models

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One key, one endpoint, 880 models across 38 model authors.

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