Model overview
This repository hosts the **gemma-4-multimodal** models exported for the React Native ExecuTorch library as ExecuTorch `.pte` programs, ready to run on device. The XNNPACK export uses mixed precision: MLP and language-model head linears use 8da4w, while attention projections and the PLE residual output projections remain fp16. Token embeddings remain int4. The small PLE context projection weights are materialized from their quantized values before lowering to preserve dequantization semantics. The model filename and runtime API remain unchanged; maximum prefill is 512 tokens and context length is 4,096 tokens. These files are published for the **ExecuTorch v1.4.1** runtime. ExecuTorch gives no forward compatibility guarantee, so an older runtime may fail to load them.
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：gemma。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。