BottleCap AI · Downloadable model subject to license terms
ThinkingCap-Qwen3.8-27B
A modification of Qwen3.8-27B focused on shorter internal task processing.
- Costs
- Self-hosting costs. Commercial licensing under the terms of BottleCap AI; no uniform public price is listed.
- Speed
- We have not independently measured speed on a comparable basis.
- Availability
- Hugging Face after accepting the access terms. PolyForm Small Business 1.0.0 license and additional permission for personal use.
- Input length
- Not independently verified in this profile.
- Inputs
- Text and images → text
Data checked . Release date unverified. Specifications and prices are provided by the vendor; usage recommendations come from the editorial team. We do not yet have our own comparative test of this version.
Ideal use
When to choose it
- Testing the model on your own hardware
- Token usage comparison with the default model
Usage boundaries
When to choose another model
- This is not an unrestricted Apache 2.0 license; check the terms for your use.
- Lower token usage does not mean higher accuracy on every task.
Traceable supporting sources
Data and measurement sources
Distinguish between the manufacturer's documentation and the results of a specific test. Measurements also depend on the settings and the task set used.
Vendor documentation
Specifications, availability, and termsManufacturer data verified as of the review date. Recommended use is an editorial interpretation.
Open original source ↗Vendor measurement
Average accuracy of 85.8% versus 86.6% for the baseline model; an average 37% reduction in reasoning tokens.These results come from BottleCap AI, not an independent acceptance test. Benefits vary by task.
Open original source ↗Efficiency in practice
With what ThinkingCap-Qwen3.8-27B combine
Sensitive data under your own control
The sensitive part stays on your own server, and the online service receives only the necessary data.
First, check the license for your intended use. Being able to run a model yourself does not in itself guarantee privacy. Server security and what data is stored also matter.Trends over time
Related events from AI Radar
BottleCap AI releases ThinkingCap-Qwen3.8-27B model with reduced thinking token consumption
Developers and individuals working with open-source LLMs now have access to a free, downloadable model with lower token consumption at comparable accuracy, which can be deployed locally in several formats.
According to the manufacturer's claims, companies running reasoning models based on Qwen can reduce thinking token consumption during inference, which translates into operating cost savings, without having to change model providers.
Next step
Compare the model using your actual task.
A benchmark narrows the selection. A short trial on your data determines the choice.