MODEL PROFILE

KrynexAI-1.4-150M-Mobile-Model

KrynexLabs · KrynexAI-1.4-150M-Mobile-Model

KrynexAI 1.4 is a compact, ultra-lightweight 150M-parameter language model designed for high-efficiency text generation, fast inference, and on-device deployment. KrynexAI 1.4 features an optimized Llama-based architecture trained on a multi-trillion token mix of web content, code, and educational data. It provides strong base capabilities in reasoning, instruction following, and general text processing while maintaining a minimal memory footprint (~270 MB weights). * **Architecture:** Llama-based Transformer Decoder * **Parameters:** ~150M * **Context Window:** 8,192 tokens * **Precision:** `bfloat16` / `fp16` Original author: SmolLM (135M). **Warning:** This repository may contain inaccurate, outdated, or otherwise unsuitable files. After fine-tuning, approximately half of the original files were left unchanged, so their contents may not reflect the current state of the project or may no longer be relevant.

Text generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/11/2 19:16:46
OVERVIEW

Model overview

KrynexAI 1.4 is a compact, ultra-lightweight 150M-parameter language model designed for high-efficiency text generation, fast inference, and on-device deployment. KrynexAI 1.4 features an optimized Llama-based architecture trained on a multi-trillion token mix of web content, code, and educational data. It provides strong base capabilities in reasoning, instruction following, and general text processing while maintaining a minimal memory footprint (~270 MB weights). * **Architecture:** Llama-based Transformer Decoder * **Parameters:** ~150M * **Context Window:** 8,192 tokens * **Precision:** `bfloat16` / `fp16` Original author: SmolLM (135M). **Warning:** This repository may contain inaccurate, outdated, or otherwise unsuitable files. After fine-tuning, approximately half of the original files were left unchanged, so their contents may not reflect the current state of the project or may no longer be relevant.

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.

PRICING & COST

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 / channelInputOutputBilling unitCollected 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.

INDEPENDENT BENCHMARKS

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。