Model overview
We first perform SFT using: * Magpie-Align/Magpie-Pro-MT-300K-v0.1 * Magpie-Align/Magpie-Reasoning-150K * Magpie-Align/Magpie-Qwen2-Pro-200K-Chinese * **SFT Model Checkpoint:** Magpie-Align/Llama-3-8B-Magpie-Align-SFT-v0.3 The overall performance is much better than the official Llama-3-8B-Instruct Model! Plus, it can answer Chinese queries frequently, thanks to our new Chinese instruction dataset! We compare our Llama-3-8B-Magpie-Align with official and other **open-aligned LLMs** that have been fine-tuned from base models and have publicly released their training datasets. The results are as follows:
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：llama3。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。