MODEL PROFILE

needle3

Cactus-Compute · needle3

A foundation model for mobiles, wearables, robots, smart home, automotive and microcontrollers. The whole model is a single 8-29 MB file, and we trade general chat capacity to beat models 10x its size on mobile tool calls and match 2-3x bigger models on extraction. - **Tool calls**: given the functions your app exposes, Needle picks the right ones and fills every argument from what the user said. Ask for two things and you get two calls in order; ask for something no tool covers and you get an empty list, not a guess. - **Structured extraction**: declare a shape, hand over messy text, get typed fields back: an invoice, a booking, a notification, a form. The decode grammar guarantees the output parses, and extraction generalises to classification. - **Text embedding**: the same model returns a vector for a sentence, so an app can search, match and route locally. The same engine also runs Whistle, our 16.9 MB speech-to-text model in seven languages. Load `whistle.cact` beside `needle3.cact` and the one binary transcribes a clip on its own, or answers it against your tools in a single call and returns the calls and the transcript in one JSON object.

Text generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/29 18:28:41
OVERVIEW

Model overview

A foundation model for mobiles, wearables, robots, smart home, automotive and microcontrollers. The whole model is a single 8-29 MB file, and we trade general chat capacity to beat models 10x its size on mobile tool calls and match 2-3x bigger models on extraction. - **Tool calls**: given the functions your app exposes, Needle picks the right ones and fills every argument from what the user said. Ask for two things and you get two calls in order; ask for something no tool covers and you get an empty list, not a guess. - **Structured extraction**: declare a shape, hand over messy text, get typed fields back: an invoice, a booking, a notification, a form. The decode grammar guarantees the output parses, and extraction generalises to classification. - **Text embedding**: the same model returns a vector for a sentence, so an app can search, match and route locally. The same engine also runs Whistle, our 16.9 MB speech-to-text model in seven languages. Load `whistle.cact` beside `needle3.cact` and the one binary transcribes a clip on its own, or answers it against your tools in a single call and returns the calls and the transcript in one JSON object.

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.

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Estimate monthly base token costs

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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。

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Frequently asked questions

Do open weights permit free commercial use?

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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。