Hunyuan Models

5 modelsGeneral models from $0.16/M inputUp to 256K context

Usage

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

Tokens

1.6B

Requests

19.8K

Models in use

5 of 5

Tokens per day, stacked by model

0112M223M07-2207-2908-0508-1208-192026-07-22 — 26,194,360 tokens hy3: 26,188,610 tencent/Hunyuan-MT-7B: 3,905 hy3-preview: 1,8452026-07-23 — 61,426,370 tokens hy3: 56,462,935 hy3-preview: 4,118,735 hy-3d-3.1: 833,250 tencent/Hunyuan-MT-7B: 11,4502026-07-24 — 223,200,765 tokens hy3-preview: 128,568,755 hy3: 94,627,750 tencent/Hunyuan-MT-7B: 3,905 tencent/Hunyuan-A13B-Instruct: 3552026-07-25 — 34,724,620 tokens hy3: 34,724,6202026-07-26 — 11,232,375 tokens hy3: 11,227,005 hy3-preview: 4,600 tencent/Hunyuan-MT-7B: 7702026-07-27 — 63,144,575 tokens hy3: 63,011,385 hy3-preview: 121,475 tencent/Hunyuan-A13B-Instruct: 10,880 tencent/Hunyuan-MT-7B: 8352026-07-28 — 213,100,060 tokens hy3: 212,569,155 hy3-preview: 526,325 tencent/Hunyuan-MT-7B: 4,460 tencent/Hunyuan-A13B-Instruct: 1202026-07-29 — 120,068,380 tokens hy3: 119,935,920 hy3-preview: 107,275 tencent/Hunyuan-MT-7B: 25,1852026-07-30 — 96,116,450 tokens hy3: 96,102,465 tencent/Hunyuan-MT-7B: 8,135 hy3-preview: 3,540 tencent/Hunyuan-A13B-Instruct: 2,3102026-07-31 — 71,883,405 tokens hy3: 71,835,480 hy3-preview: 44,635 tencent/Hunyuan-MT-7B: 3,2902026-08-01 — 11,778,695 tokens hy3: 11,778,470 tencent/Hunyuan-MT-7B: 2252026-08-02 — 12,660,305 tokens hy3: 12,659,510 tencent/Hunyuan-MT-7B: 530 hy3-preview: 2652026-08-03 — 22,430,265 tokens hy3: 21,344,795 hy3-preview: 1,047,440 tencent/Hunyuan-MT-7B: 38,0302026-08-04 — 116,711,225 tokens hy3: 115,905,715 hy3-preview: 772,325 tencent/Hunyuan-MT-7B: 19,240 tencent/Hunyuan-A13B-Instruct: 13,9452026-08-05 — 63,075,145 tokens hy3: 63,046,610 tencent/Hunyuan-MT-7B: 17,130 hy3-preview: 11,4052026-08-06 — 33,870,465 tokens hy3: 33,863,790 tencent/Hunyuan-MT-7B: 6,015 tencent/Hunyuan-A13B-Instruct: 6602026-08-07 — 59,303,490 tokens hy3: 59,295,680 tencent/Hunyuan-MT-7B: 4,155 hy3-preview: 3,6552026-08-08 — 9,868,600 tokens hy3: 9,864,985 tencent/Hunyuan-MT-7B: 3,6152026-08-09 — 4,611,335 tokens hy3: 4,602,125 tencent/Hunyuan-MT-7B: 9,2102026-08-10 — 66,856,290 tokens hy3: 66,847,315 hy3-preview: 3,890 tencent/Hunyuan-A13B-Instruct: 3,430 tencent/Hunyuan-MT-7B: 1,6552026-08-11 — 62,112,215 tokens hy3: 43,479,895 hy-3d-3.1: 18,541,980 hy3-preview: 80,915 tencent/Hunyuan-MT-7B: 7,610 tencent/Hunyuan-A13B-Instruct: 1,8152026-08-12 — 13,809,190 tokens hy3: 7,925,975 hy3-preview: 5,874,460 tencent/Hunyuan-MT-7B: 6,195 tencent/Hunyuan-A13B-Instruct: 2,5602026-08-13 — 56,712,090 tokens hy3: 56,707,600 tencent/Hunyuan-MT-7B: 4,4902026-08-14 — 13,170,260 tokens hy3: 13,034,910 hy3-preview: 134,800 tencent/Hunyuan-MT-7B: 5502026-08-15 — 6,626,400 tokens hy3: 6,621,765 tencent/Hunyuan-MT-7B: 3,960 hy3-preview: 540 tencent/Hunyuan-A13B-Instruct: 1352026-08-16 — 7,298,380 tokens hy3: 7,294,875 tencent/Hunyuan-MT-7B: 3,5052026-08-17 — 19,284,260 tokens hy3: 10,927,675 hy-3d-3.1: 8,332,500 tencent/Hunyuan-A13B-Instruct: 17,355 hy3-preview: 6,7302026-08-18 — 30,327,500 tokens hy-3d-3.1: 18,748,500 hy3: 11,553,770 hy3-preview: 23,925 tencent/Hunyuan-MT-7B: 1,3052026-08-19 — 17,909,200 tokens hy3: 8,753,800 hy-3d-3.1: 5,832,750 hy3-preview: 3,322,390 tencent/Hunyuan-MT-7B: 2602026-08-20 — 83,854,550 tokens hy3: 50,489,900 hy3-preview: 31,489,650 hy-3d-3.1: 1,875,000
  • hy3
  • hy3-preview
  • hy-3d-3.1
  • tencent/Hunyuan-MT-7B
  • tencent/Hunyuan-A13B-Instruct

Which models that traffic went to

  1. Hy385.9%1.4B
  2. Hy3 Preview10.8%176M
  3. Hy 3d 3.13.3%54.2M
  4. tencent/Hunyuan-MT-7B<0.1%190K
  5. tencent/Hunyuan-A13B-Instruct<0.1%53.6K

Share of 1.6B 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 Hunyuan Models

Open in model list
Hunyuan 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
hy3Takes text, returns text.256K128K$0.16$0.62/M$0.04/M66 tok/s3.40 s
hy3-previewTakes text, returns text.256K128K$0.17$0.57/M$0.05/M40 tok/s2.05 s
hy-3d-3.1Takes text, vision. Output modality not published.FreeFree/M
tencent/Hunyuan-A13B-Instruct$0.14$0.56/M
tencent/Hunyuan-MT-7B$0.20$0.20/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.

Hunyuan on AIHubMix

Which Hunyuan model should I start with?

hy3 at $0.16/M input — the cheapest entry here that declares tool calling, and it carries a 256K context. Move up to tencent/Hunyuan-MT-7B when answer quality matters more than cost, or to hy3-preview for long-form reasoning.

Which of these models reason before answering?

2 of the 5 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 (tencent/…), 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 hy3 bills cache hits at 25% of the input rate and hy3-preview bills cache hits at 30% 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 Hunyuan 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.

Start calling Hunyuan in one line

One key, one endpoint, 859 models across 37 model authors.