Model overview
**Inferact/MiniMax-M3-EAGLE3** is an EAGLE3 draft model for accelerating inference of MiniMax-M3. It is served end-to-end with **vLLM** and was trained using **TorchSpec** — a torch-native online speculative-decoding training framework that runs FSDP training and vLLM-based target inference concurrently, learning from **MiniMax-M3-regenerated responses and live vLLM-generated hidden states** to match the base model's exact token distribution. The draft is a **1-layer** dense Llama (`LlamaForCausalLMEagle3`, ~3.3 B params) operating on MiniMax-M3's `hidden_size=6144` / `vocab_size=200064`; at serve time it shares the target's embedding and LM head (EAGLE3). See `config.json` for the full architecture. All numbers are measured end-to-end against `MiniMaxAI/MiniMax-M3-MXFP8` served with vLLM at `tensor-parallel-size=4`, `num_speculative_tokens=3`, and `--enforce-eager`. Greedy draft sampling (`topk=1`).
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。
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Do open weights permit free commercial use?
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Are these real-time billing prices?
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Sources & traceability
许可证:mit。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。