Model overview
This repository contains LiteRT-LM variants of Qwen/Qwen3-1.7B optimized for on-device text generation. `Qwen3-1.7B_dynamic_wi4b32_afp32.litertlm` is a dynamic INT4 variant (block-32 weights, FP32 activations). It was converted through the LiteRT Torch (`litert-torch`) path and quantized with AI Edge Quantizer. This artifact incorporates LiteRT-LM GPU graph optimizations, including composite ops for RoPE, fused QKV, and fused Gate/Up projections, and is configured with static prefill memory allocation. Both files: Need litert-lm 0.18.0 or newer (tested on 0.18.0) and carry LiteRT-LM's official qwen3 configuration, so thinking is on unless `enable_thinking` is false, the reasoning arrives on the thought channel, and tool calls are parsed by the runtime.
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。