Hunyuan Models

7 modelsGeneral models free to startUp to 1.05M context

Usage

Last 30 days · 2026-08-09 to 2026-09-07

Tokens

4.7B

Requests

59.5K

Models in use

7 of 7

Tokens per day, stacked by model

0466M933M08-0908-1608-2308-3009-062026-08-09 — 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: 1,875,0002026-08-21 — 77,727,080 tokens hy3: 77,723,070 tencent/Hunyuan-MT-7B: 4,0102026-08-22 — 20,319,425 tokens hy3: 20,309,110 tencent/Hunyuan-MT-7B: 9,350 hy3-preview: 9652026-08-23 — 16,348,640 tokens hy3: 16,347,835 tencent/Hunyuan-MT-7B: 700 hy3-preview: 1052026-08-24 — 222,074,930 tokens hy3: 222,062,770 hy3-preview: 9,650 tencent/Hunyuan-MT-7B: 2,5102026-08-25 — 24,184,350 tokens hy3: 24,178,820 hy3-free: 2,610 tencent/Hunyuan-A13B-Instruct: 2,560 hy3-preview: 3602026-08-26 — 249,766,565 tokens hy3-free: 243,988,760 hy3: 5,766,260 tencent/Hunyuan-A13B-Instruct: 10,920 hy3-preview: 455 tencent/Hunyuan-MT-7B: 1702026-08-27 — 438,452,620 tokens hy3-free: 365,441,270 hy3: 73,008,890 tencent/Hunyuan-MT-7B: 2,4602026-08-28 — 923,627,565 tokens hy3-free: 539,957,675 hy4-preview: 358,613,565 hy3: 24,982,195 hy3-preview: 74,1302026-08-29 — 79,120,205 tokens hy4-preview: 50,360,425 hy3-free: 23,509,365 hy3: 5,239,230 hy3-preview: 6,685 tencent/Hunyuan-MT-7B: 4,5002026-08-30 — 43,590,085 tokens hy3-free: 22,941,040 hy4-preview: 17,413,520 hy-3d-3.1: 2,499,995 hy3: 734,620 hy3-preview: 615 tencent/Hunyuan-MT-7B: 2952026-08-31 — 677,923,605 tokens hy4-preview: 596,596,890 hy3-preview: 47,848,165 hy3: 33,474,740 tencent/Hunyuan-MT-7B: 3,660 tencent/Hunyuan-A13B-Instruct: 1502026-09-01 — 137,425,270 tokens hy4-preview: 69,420,500 hy3-preview: 36,847,960 hy3: 23,653,995 hy-3d-3.1: 7,500,000 tencent/Hunyuan-MT-7B: 2,680 tencent/Hunyuan-A13B-Instruct: 1352026-09-02 — 76,436,685 tokens hy4-preview: 41,631,505 hy3: 24,587,555 hy-3d-3.1: 9,791,995 hy3-preview: 423,240 tencent/Hunyuan-A13B-Instruct: 1,415 tencent/Hunyuan-MT-7B: 9752026-09-03 — 113,530,335 tokens hy3: 103,068,255 hy4-preview: 8,640,550 hy3-preview: 1,778,470 tencent/Hunyuan-A13B-Instruct: 34,280 tencent/Hunyuan-MT-7B: 8,7802026-09-04 — 932,943,170 tokens hy3: 813,383,200 hy4-preview: 115,179,990 hy-3d-3.1: 4,375,240 tencent/Hunyuan-MT-7B: 4,610 hy3-preview: 1302026-09-05 — 29,590,310 tokens hy4-preview: 29,072,290 hy3: 517,330 tencent/Hunyuan-MT-7B: 395 hy3-preview: 2952026-09-06 — 91,137,700 tokens hy3: 79,110,755 hy3-preview: 11,897,700 hy4-preview: 115,545 tencent/Hunyuan-MT-7B: 13,565 tencent/Hunyuan-A13B-Instruct: 1352026-09-07 — 199,078,305 tokens hy3: 168,070,785 hy3-preview: 30,998,925 tencent/Hunyuan-MT-7B: 5,920 hy4-preview: 2,675
  • hy3
  • hy4-preview
  • hy3-free
  • hy3-preview
  • hy-3d-3.1
  • tencent/Hunyuan-MT-7B
  • tencent/Hunyuan-A13B-Instruct

Which models that traffic went to

  1. Hy342.3%2B
  2. Hy4 Preview27.2%1.3B
  3. Hy3 (free)25.3%1.2B
  4. Hy3 Preview3.6%171M
  5. Hy 3d 3.11.6%77.5M
  6. tencent/Hunyuan-MT-7B<0.1%103K
  7. tencent/Hunyuan-A13B-Instruct<0.1%74.9K

Share of 4.7B 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 7 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

All 7 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
hy4-previewTakes text, returns text.1.05M64K$0.845$2.535/M$0.0423/M17 tok/s2.34 s
hy3-freeTakes text, returns text.256K128KFreeFree/M
hy3Takes text, returns text.256K128K$0.1562$0.6248/M$0.0391/M75 tok/s3.90 s
hy3-previewTakes text, returns text.256K128K$0.17$0.5667/M$0.051/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$0.2$0.2/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.

Hunyuan on AIHubMix

Which Hunyuan model should I start with?

hy3-free is free on input — the cheapest entry here that declares tool calling, and it carries a 256K context. Move up to hy4-preview when answer quality matters more than cost.

Which of these models reason before answering?

4 of the 7 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 hy4-preview bills cache hits at 5% of the input rate and hy3 bills cache hits at 25% 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, 880 models across 38 model authors.