Tencent's HunyuanVideo, a 13B open-weights text-to-video diffusion transformer. Produces high-motion, photorealistic clips with smooth temporal consistency and was one of the first open models to rival closed systems on motion quality.
KĂ€ivitamisel reserveeritakse 9,18Â $ (918 krediiti); arveldatakse tegelik GPU aeg.
Kontode puhul, millel pole ostuajalugu: kĂ€ivitused ĂŒle 2 krediidi vajavad tĂ€iendust.
Oled siin uus?
10 tasuta krediiti (0,10Â $), kui registreeritud Google'iga
Kasutatav 24 tundi pÀrast registreerimist, kuni 5 kÀivitust pÀevas ja maksimaalselt 2 krediiti kÀivituse kohta. Muud sisselogimismeetodid algavad ilma krediitideta.
02
Examples
Real outputs from the public examples of this model on Replicate, with the prompt and settings that produced them. They were not generated live on this page.
Prompt
A cat walks on the grass, realistic style
Pikkus: 0:05
Settings
width
864
height
480
fps
24
Prompt
Close-up, A little girl wearing a red hoodie in winter strikes a match. The sky is dark, there is a layer of snow on the ground, and it is still snowing lightly. The flame of the match flickers, illuminating the girl's face intermittently.
Pikkus: 0:05
Settings
width
864
height
480
fps
24
Prompt
a stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse. She wears
sunglasses and red lipstick. She walks confidently and casually. The street is damp and reflective, creating a mirror effect of the colorful lights. Many pedestrians walk about.
Pikkus: 0:05
Settings
width
864
height
480
fps
24
NĂ€ite-prompid
NĂ€ited Railwail kataloogist. Neid ei loodud otse sellel lehel.
Underwater Scene
Pikkus: 0:08
Camera gliding through a vibrant coral reef teeming with tropical fish, sunlight filtering through the crystal-clear water creating dancing light patterns on the ocean floor, documentary style
Fantasy Animation
Pikkus: 0:06
A tiny glowing fairy emerging from an opening flower bud in an enchanted forest, sparkles trailing behind her wings as she takes flight, magical atmosphere with bioluminescent plants
03
Teave: HunyuanVideo
LĂŒhidaltSeisuga 23. september 2026
HunyuanVideo on mudel, mille on vĂ€lja töötanud Tencent kategoorias Videote genereerimine. Railwail'is maksab HunyuanVideo â 3,06 $ kĂ€ivituse kohta.
HunyuanVideo from Tencent is a large open-source text-to-video model built on a DiT architecture with a unified full-attention design. It is known for realistic physics, large-scale motion and good text alignment, and ships its own weights, making it a popular base for fine-tuning and LoRA training.
Taust
Teave Tencent kohta
Asutatud 1998 · Shenzhen, China
Tencent Holdings is one of the largest technology and entertainment conglomerates in the world, founded in 1998 by Ma Huateng (Pony Ma) and four co-founders in Shenzhen. Tencent's AI Lab, founded in 2016, and the Hunyuan team (the company's foundation-model group) developed the Hunyuan family of text, image, 3D and video models. HunyuanVideo (released December 2024 with the 13B foundation model open-sourced) was the largest publicly released open-weight video diffusion model at the time, and rapidly became a popular base for community fine-tunes (LoRAs, control nets, audio-driven extensions). The model is hosted on Hugging Face and GitHub under a custom licence that allows research and limited commercial use.
Diffusion Transformer with dual-stream design (separate text/video streams)
HunyuanVideo is a 13B-parameter Diffusion Transformer (DiT) operating on a 3D causal VAE latent. Its denoiser uses a dual-stream / single-stream design inspired by FLUX-1: dedicated text and video streams first process their modalities separately and then concatenate for joint self-attention. Text conditioning combines a CLIP-like vision-language encoder and a multilingual large-language-model text encoder (MLLM) for stronger prompt understanding, especially on long captions. The model is trained with Flow Matching and 3D Rotary Position Embeddings, and uses a progressive curriculum from images to short videos to long videos at 720p / 24 fps. The accompanying paper details a meticulously curated multi-billion-clip dataset with hierarchical filtering and dense bilingual captions. HunyuanVideo supports text-to-video natively and the open release includes a high-quality 5-second / 720p model; community follow-ups added image-to-video, audio-driven and longer-duration variants.
Parameetrid
13 billion
VÔimalused
13B open-weight text-to-video model (one of the largest released openly)
Generates ~5-second clips at 720p / 24 fps natively
Bilingual Chinese/English prompt handling via MLLM text encoder
Dual-stream DiT architecture inspired by FLUX-1
Strong prompt adherence on long, dense captions
Active community ecosystem (image-to-video, LoRAs, audio-sync)
Runs on 60-80 GB GPU memory (FP16), 40 GB with optimisations
Permissive licence for non-commercial research and limited commercial use
Best for: open-source video pipelines, research, on-prem creative tooling.
Treening ja litsents
Multi-billion-clip curated video corpus with hierarchical aesthetic, motion and caption-quality filtering, plus dense bilingual captions produced by an in-house MLLM captioner.
Litsents: Tencent Hunyuan Community Licence: weights free for research and limited commercial use with attribution; restrictions apply above thresholds and for certain jurisdictions.
Turvalisuse testimine: Released with safety filtering during training and a recommended NSFW classifier for deployment; subject to Chinese CAC algorithmic-content rules on Tencent-hosted surfaces.
Teadaolevad piirangud
Native duration ~5 seconds
720p only (extensions require upscalers)
High VRAM requirements vs smaller open models
No native audio
Licence has thresholds for very large commercial deployers
Hinnad USA dollarites. Kasutamine arvestatakse eelmakstud krediitidest.
TĂŒĂŒpiline kĂ€ivitus (â 418 s 4x H100 peal)
3,06 $ kÀivituse kohta
GPU-aeg (4x H100)
0,00732Â $ GPU-sekundi kohta
Arvestatakse GPU-aeg, mida kĂ€ivitus tegelikult vĂ”tab. KĂ€ivituse alustamisel reserveeritakse sinu saldost 3Ă tĂŒĂŒpiline hind ja arvutatakse hiljem.
1 krediit = 0,01Â $
Kulukalkulaator
Hinna kalkulaator
s
Pakkuja andmetel tĂŒĂŒpiline: umbes 418 s
Kokku
306,00Â $
30Â 600 krediiti
KĂ€ivituse kohta
3,06 $ · 306 krediiti
Arvestatakse tegelik GPU-aeg; see on hinnang.
05
API
Kutsu HunyuanVideo oma Railwail API vÔtmega. Kasuta selles pÀringus seda mudeli ID-d:
curl https://railwail.com/api/v1/videos/generations \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "hunyuan-video",
"prompt": "A slow drone shot over a misty pine forest at sunrise"
}'
# Response: {"job_id": "...", "status": "queued", ...}
# Poll until status is completed, failed or cancelled:
curl https://railwail.com/api/v1/jobs/JOB_ID \
-H "Authorization: Bearer $RAILWAIL_API_KEY"
import os
import time
import requests
API = "https://railwail.com/api/v1"
headers = {"Authorization": f"Bearer {os.environ['RAILWAIL_API_KEY']}"}
job = requests.post(
f"{API}/videos/generations",
headers=headers,
json={
"model": "hunyuan-video",
"prompt": "A slow drone shot over a misty pine forest at sunrise",
},
).json()
while True:
status = requests.get(f"{API}/jobs/{job['job_id']}", headers=headers).json()
if status["status"] in ("completed", "failed", "cancelled"):
break
time.sleep(5)
print(status["status"], status.get("output_url"))
const API = "https://railwail.com/api/v1";
const headers = {
Authorization: `Bearer ${process.env.RAILWAIL_API_KEY}`,
"Content-Type": "application/json",
};
const job = await fetch(`${API}/videos/generations`, {
method: "POST",
headers,
body: JSON.stringify({
model: "hunyuan-video",
prompt: "A slow drone shot over a misty pine forest at sunrise"
}),
}).then((r) => r.json());
let status;
do {
await new Promise((r) => setTimeout(r, 5000));
status = await fetch(`${API}/jobs/${job.job_id}`, { headers }).then((r) => r.json());
} while (!["completed", "failed", "cancelled"].includes(status.status));
console.log(status.status, status.output_url);
Tencent Hunyuan Community Licence: weights free for research and limited commercial use with attribution; restrictions apply above thresholds and for certain jurisdictions.
Kataloogi kirje uuendatud
23. september 2026
Sisendparameetrid
Mudeli sisendiskeemi sisendid ja seaded. API nÀide jaotises API nÀitab, milliseid neist API aktsepteerib.
HunyuanVideo on mudel, mille töötas vÀlja Tencent kategoorias Videote genereerimine. Railwail'is saad seda kutsuda API vÔtme abil Railwail API kaudu.
Kui palju maksab HunyuanVideo Railwail'is?
Railwail'is maksab HunyuanVideo â 3,06 $ kĂ€ivituse kohta. Sulle arvestatakse see, mida iga pĂ€ring tegelikult kasutab. Kasutamine makstakse eelnevalt ostetud krediitidest; 1 krediit vĂ”rdub 0,01 $.
Milliseid seadistusi HunyuanVideo toetab?
Vastavalt sisendiskeemile teab HunyuanVideo neid parameetreid: prompt (kuni 2000 tÀhemÀrki) ja seed.
Kui kiire on HunyuanVideo?
HunyuanVideo kohta ei ole Railwail'is veel piisavalt mÔÔdetud kÀivitusi, et kÀivitusaega vÀita. See sÔltub sisendist, seadistustest ja pakkuja koormusest.
Kas HunyuanVideo on parem kui Google Veo 3.1?
See sĂ”ltub ĂŒlesandest. HunyuanVideo (Tencent) ja Google Veo 3.1 (Google DeepMind) on mĂ”lemad mudelid kategoorias Videote genereerimine. VĂ”rdlusleht nĂ€itab nende hindu ja spetsifikatsioone kĂ”rvuti.
