Model overview
Drag this image into ComfyUI to load the example workflow. I've done limited testing so far on running the model, so take that workflow and the following advice with a grain of salt. bigASP V2.5 is an intermediary experiment I wanted to run while I prepared for V3. Like V2, it is a large scale finetune from SDXL, and follows most of V2's approach except for these bizarre tweaks: 1. Dataset expanded from 6.7M to 13M images by including additional sources as well as, significantly, anime. Why? Because I wanted to see if the model could dual purpose for both photoreal gens and anime gens. Also I wanted to see if photoreal gens could benefit from the more varied concepts present in anime/furry/etc images. 2. Training length expanded from 40M samples to 150M samples. One of my theories for the tempermental behavior of V2 is the scale of the training. Models like Pony v6 had a much larger amount of training. 150M samples brings V2.5 within the ballpark of that class of model. 3. Using JoyCaption Beta One instead of the Pre-Alphas used in V2. Beta One has more modes, and I tweaked its language and verbage quite a bit, so hopefully V2.5 is less sensitive to prompts. 4. Swapping SDXL's training objective over to Rectified Flow Matching like more modern models (i.e. Flux, Chroma, etc). This was done for two reasons. One, Flow Matching makes higher quality generations. And two, it allowed me to ditch SDXL's broken noise schedule. That latter bit greatly enhances the model's ability to control the overall structure of generations, resulting in less mangled mess generations and extra limbs. It also allows V2.5 to generate more dynamic range from very dark images to very bright images.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：来源未披露，须进一步核验。模型介绍与第三方评测均以原来源的具体版本和方法为准。