Sora 1 vs Llama 4 405B

Sora 1 and Llama 4 405B come from different camps — OpenAI versus Meta — and they split most sharply on price and context. Sora 1 runs at $0.50/$2.00 per 1M tokens with a — window; Llama 4 405B sits at $1.30/$5.00 with 256K of context. Neither is objectively "better" — the right pick depends on what you're shipping.

In practice: OpenAI's video generation model. Create realistic videos from text prompts or images. Ideal for creative content, marketing videos, and visual prototyping. Meta's largest open-weight model with 405 billion parameters. Near-frontier performance on reasoning and coding tasks. Available through AI API Hub with pay-as-you-go pricing. Both ship through AI API Hub on an OpenAI-compatible endpoint, so you can move between them by changing a single model name — and settle the bill with USDT or USDC, no credit card required.

On cost alone, Sora 1 is the cheaper of the two (Save $0.80 per 1M input), which adds up fast once real traffic hits. Use the calculator below to model your own volume.

→If your workload involves long document reasoning or multi-step instruction following → Llama 4 405B performs better with its 256K context.

→If cost is your primary constraint → Sora 1 provides ~62% lower cost per 1M tokens.

On performance, Sora 1 leans into text-to-video and pairs it with — of context — enough for text-to-video and image-to-video. Llama 4 405B answers with open-weight across 256K, which makes it the stronger fit when you need open-weight and 405b parameters. The gap is real, but it's a question of fit rather than dominance.

Pricing is where they part ways. At $0.50/$2.00 versus $1.30/$5.00 per 1M tokens, Sora 1 is the clear budget pick. Run a typical workload of 1M requests/month at ~1K input / 500 output tokens and Sora 1 keeps roughly $2300.00/month in your pocket.

Our take: if cost efficiency drives the decision, Sora 1 wins. Either way, both run through AI API Hub with USDT/USDC payments and instant activation — start with $5 and one API key covers every model.

Since both Sora 1 and Llama 4 405B are available through AI API Hub with OpenAI-compatible API format, switching between them requires only changing the model name parameter. Your existing SDK code works without modification.

from openai import OpenAI
client = OpenAI(api_key="YOUR_KEY", base_url="https://api.apiyihe.org/v1")
# Before: response = client.chat.completions.create(model="sora-1", messages=[...])
# After:  response = client.chat.completions.create(model="llama-4-405b", messages=[...])

import OpenAI from "openai";
const client = new OpenAI({apiKey: process.env.KEY, baseURL: "https://api.apiyihe.org/v1"});
// Before: model: "sora-1"
// After:  model: "llama-4-405b"

curl https://api.apiyihe.org/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -d '{"model": "llama-4-405b", "messages": [{"role":"user","content":"Hello"}]}'

💡 AI API Hub supports both models through one API key. No separate accounts needed. Pay with USDT/USDC for all models.