Model overview
The NVIDIA-Nemotron-3.5-Bolt-E4B-4GB-DFlash model is the GGUF (a binary model file format used by llama.cpp) version of NVIDIA-Nemotron-3.5-Bolt-E4B-BF16-DFlash, the DFlash speculative decoding draft checkpoint for NVIDIA-Nemotron-3.5-Bolt-E4B, a reasoning language model post-trained by NVIDIA from Google's Gemma 4 E4B IT. It is converted to GGUF in BF16 (bfloat16) for use with llama.cpp and must be loaded together with the GGUF version of the target model, Nemotron-3.5-Bolt-E4B-4GB. The draft model does not include token embeddings or an output head, and uses those of the target model at runtime. The model is intended for lower-latency local serving of NVIDIA-Nemotron-3.5-Bolt-E4B on workstation GPUs. Developers running NVIDIA-Nemotron-3.5-Bolt-E4B locally with llama.cpp for reasoning, chat, tool use, and agentic workflows that benefit from lower-latency speculative decoding on workstation GPUs. This release is intended for DFlash-assisted serving together with NVIDIA-Nemotron-3.5-Bolt-E4B-GGUF rather than as a standalone model checkpoint. **Architecture Type:** Transformer **Network Architecture:** Other - DFlash draft model (five Qwen3-style decoder layers) **Number of Model Parameters:** 360M (360,480,000), stored in BF16 in a single GGUF file of 736,812,096 bytes (736.81 MB / 702.68 MiB). The draft model shares the token embeddings and output head of the target model, so they are not included in this checkpoint.
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.
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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：other。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。