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qwen-360-diffusion

ProGamerGov

Qwen 360 Diffusion is a rank 128 LoRA built on top of a 20B parameter MMDiT (Multimodal Diffusion Transformer) model, designed to generate 360 degree equirectangular projection images from text descriptions. The model was trained from the Qwen Image model on an extremely diverse dataset composed of tens of thousands of equirectangular images, depicting landscapes, interiors, humans, animals, and objects. All images were resized to 2048x1024 before training. The model was also trained with a diverse dataset of normal photos for regularization, making the model a realism finetune when prompted correctly.

Image generation

Input Text→ Output Image

Price not verifiedCheck multimodal and channel pricing separately

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sdxl-360-diffusion

ProGamerGov

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Basic profile indexed · More details to follow

Image generation

Input Text→ Output Image

Price not verifiedCheck multimodal and channel pricing separately

View details ↗

CompareSource / docs ↗

COST EXPLORER

Great models. Clear costs.

Cost analysis

Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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Selection guide & FAQ

How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.