يتم حجز 1.5121 US$ (151.21 رصيد) عند البدء؛ يتم فواتير وقت GPU الفعلي.
للحسابات بدون عملية شراء سابقة: التشغيلات التي تتجاوز 2 رصيد تحتاج إلى إعادة تعبئة.
جديد هنا؟
10 رصيد مجاني (0.10 US$) عند التسجيل باستخدام Google
قابل للاستخدام 24 ساعة بعد التسجيل، حتى 5 تشغيل يومياً وبحد أقصى 2 رصيد لكل تشغيل. طرق تسجيل الدخول الأخرى تبدأ بدون رصيد.
02
Examples
Real outputs from the public examples of this model on Replicate, with the prompt and settings that produced them. They were not generated live on this page.
Prompt
Close-up of a chameleon's eye, with its scaly skin changing color. Ultra high resolution 4k.
المدة: 0:05
Settings
num_frames
121
fps
24
Prompt
A pristine snowglobe featuring a winter scene sits peacefully. The globe violently explodes, sending glass, water, and glittering fake snow in all directions. The scene is captured with high-speed photography.
المدة: 0:05
Settings
num_frames
121
fps
24
Prompt
The video opens with a close-up of a woman in a white and purple outfit, holding a glowing purple butterfly. She has dark hair and walks gracefully through a traditional Japanese-style village at night
المدة: 0:05
Settings
num_frames
121
fps
24
03
حول Mochi 1
الملخصاعتباراً من ٢٣ سبتمبر ٢٠٢٦
Mochi 1 هو نموذج من Community في فئة توليد الفيديو. على Railwail، يكلف Mochi 1 ≈ 0.5041 US$ لكل تشغيل. نسب العرض إلى الارتفاع المدعومة: 16:9 و9:16 و1:1.
الخلفية
حول Genmo
تأسس في 2023 · San Francisco, USA
Genmo was founded in 2023 by Paras Jain (CEO) and Ajay Jain (CTO), both PhDs from UC Berkeley's BAIR lab, with a focus on open-source generative video. The company released the early Replay product and the smaller GEN-1 video model before launching Mochi 1 in October 2024 as a 10B-parameter open-weight text-to-video model under the Apache 2.0 licence -- at the time the largest open-source video model with a fully permissive licence. Genmo positions Mochi 1 as a research foundation for the community to fine-tune, extend and study, in deliberate contrast to closed competitors. The company has raised over $30M from investors including NEA and the Y Combinator network.
Asymmetric Diffusion Transformer (AsymmDiT) at 10B parameters with custom 3D VAE
Mochi 1 is a 10B-parameter Asymmetric Diffusion Transformer (AsymmDiT) operating on a high-compression 3D causal Variational Autoencoder. The 'asymmetric' design uses dramatically more parameters for the video stream than for the text stream while sharing self-attention, on the hypothesis that visual modeling is the bottleneck for video generation. Position information uses 3D RoPE; the model is trained with Rectified Flow Matching at full resolution and high motion intensity. Text conditioning uses a T5-XXL encoder. Mochi 1 generates 5-second clips at 480p / 30 fps natively (with a 720p HD variant in preview at launch). Training is done on a curated, filtered video corpus with dense captions produced by an in-house captioner. The team explicitly report ablations on resolution scheduling, motion intensity filtering and caption quality.
المعاملات
10 billion
الإمكانيات
10B open-weight text-to-video model under Apache 2.0 (most permissive in class)
Asymmetric DiT design biased toward visual capacity
curl https://railwail.com/api/v1/videos/generations \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "mochi-1-genmo",
"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": "mochi-1-genmo",
"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: "mochi-1-genmo",
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);
Mochi 1 هو نموذج من Community في فئة توليد الفيديو. على Railwail يمكنك استدعاؤه باستخدام مفتاح API عبر Railwail API.
كم تكلفة Mochi 1 على Railwail؟
على Railwail، يكلف Mochi 1 ≈ 0.5041 US$ لكل تشغيل. يتم فرض رسوم عليك مقابل ما تستخدمه كل طلب فعلياً. الاستخدام يُدفع من أرصدة مدفوعة مقدماً؛ 1 رصيد يساوي ٠٫٠١ US$.
ما الإعدادات التي يدعمها Mochi 1؟
وفقاً لمخطط الإدخال الخاص به، Mochi 1 يعرف هذه المعاملات: prompt (حتى 2,000 حرف) وfps (8 إلى 30) وseed وaspect_ratio (16:9 أو 9:16 أو 1:1) وduration_sec (1 إلى 6) وmotion_strength (0 إلى 1).
ما سرعة Mochi 1؟
لا توجد عمليات تشغيل مقاسة كافية لـ Mochi 1 على Railwail حتى الآن لتحديد وقت التشغيل. يعتمد على الإدخال والإعدادات والحمل لدى المزود.
هل Mochi 1 أفضل من Google Veo 3.1؟
هذا يعتمد على المهمة. Mochi 1 (Community) و Google Veo 3.1 (Google DeepMind) كلاهما نموذج في فئة توليد الفيديو. تعرض صفحة المقارنة أسعارهما والمواصفات جنباً إلى جنب.
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.
