Model overview
YOLO26 object detection models optimized for 320x320 resolution — Ultralytics' end-to-end NMS-free architecture with the decode head compiled onto the NPU. This repo carries both the **nano (yolo26n)** and **small (yolo26s)** variants. Both models are developed and optimized for the Synaptics Astra™ **SL2610-Series processors** Torq NPU. - **Model Type:** Object Detection (NMS-free, one-to-one head) - **Input:** 1x320x320x3 int8 NHWC (scale 1/255, zero-point −128) - **Output:** 1x84x2100 int8 — rows 0-3: xywh normalized to imgsz; rows 4-83: class probabilities (already decoded on-NPU; int8 output quantization saturates confidences near 0.5, threshold accordingly) - yolo26n output dequantization: scale 0.00423651235178113, zero-point −128 - yolo26s output dequantization: scale 0.004613031819462776, zero-point −128
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：agpl-3.0。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。