ThinkingCap Qwen3.6 27B is a 27-billion-parameter reasoning model from BottleCap AI, a Prague-based lab co-founded by word2vec author TomΓ‘Ε‘ Mikolov. It is a deliberately minimal fine-tune of Alibaba's Qwen3.6-27B, trained on a curated multi-domain problem set with an objective that rewards reaching the right answer efficiently rather than rewarding correctness alone, so the model learns to stop reasoning once it has enough to answer. BottleCap reports a 50% average reduction in thinking tokens and over 90% in the best cases, with a 45.8% macro-average reduction across twelve out-of-domain benchmarks and accuracy holding or improving, including LiveCodeBench rising from 80.7% to 84.3% and GSM8K from 93.3% to 96.5% while using 74.1% fewer thinking tokens. Because reasoning traces are billed as output tokens, the saving lands directly on cost and latency for workloads that call a thinking model in a loop, such as agent steps, classification, and extraction. Style, knowledge, and safety behaviour track the Qwen3.6-27B checkpoint closely, and the weights are published on Hugging Face under Apache 2.0.
ThinkingCap Qwen3.6 27B runs on 1 route through the qynio gateway. Compare residency, zero retention, and training posture at a glance β full data-handling detail per route below.
| Provider | Region | Zero data retention | Training | Input | Output |
|---|---|---|---|---|---|
| EU | Zero data retention | No | $0.40 | $2.60 |
Each route hosting ThinkingCap Qwen3.6 27B has its own privacy posture, residency, and no-KYC terms. Postures are maintained by qynio with a last-verification timestamp.
Zero data retention is on by default on Pay-as-you-go β no action required. No training on customer data. EEA; wallets; deposit available.
Call ThinkingCap Qwen3.6 27B through the qynio gateway with one API key. Let your coding agent set it up, or call it directly β qynio is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.
Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up qynio for you.
import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.QYN_API_KEY,baseURL: "https://api.qyn.io/v3/compat",});const completion = await client.chat.completions.create({model: "sference/thinkingcap-qwen3.6-27b",messages: [{ role: "user", content: "Hello" }],});console.log(completion.choices[0].message.content);
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