Model overview
**First community NVFP4 quantization** of google/gemma-4-26B-A4B-it — the Mixture-of-Experts variant of Gemma 4 with 25.2B total parameters and only 3.8B active per token. Tested on NVIDIA DGX Spark (128GB unified memory, GB10 Blackwell, SM 12.1). Model loads at 15.7 GiB — plenty of headroom for 65K+ context with FP8 KV cache. Gemma 4 MoE stores expert weights as **fused 3D tensors** (`nn.Parameter` of shape `[128, dim, dim]`) instead of individual `nn.Linear` modules. NVIDIA Model Optimizer (modelopt) only quantizes `nn.Linear` — it silently skips the 3D expert parameters, which are 91% of the model.
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：apache-2.0。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。