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thinkingcap-qwen3.6-27b

ThinkingCap-Qwen3.6-27B is a reasoning tuned model from BottlecapAI built on Qwen3.6 27B. It supports extended thinking with tool calling and a 256K context window. Served via Sference.

ReasoningTool calling
CompareDocs

Specifications

Context window262K tokens
Max output33K tokens
API typechat
AddedJul 13, 2026
Model IDsference/thinkingcap-qwen3.6-27b
Data retentionNo
Used for trainingNo
Provider location🇪🇺 EU (Finland)
Privacy policysference Privacy Policy→

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model. Check the base model page or the sference models overview.

Pricing

Input / 1M
$0.40
Output / 1M
$3.00
Cache write
N/A
Cache read
N/A
Estimated cost
100K input + 10K output$0.0700
1M input + 100K output$0.70
10M input + 1M output$7.00

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to sference/thinkingcap-qwen3.6-27b.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="sference/thinkingcap-qwen3.6-27b",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Other sference models

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33K ctx$0.05/1M
glm-5.2
1.0M ctx$1.20/1M
Coding 69

Frequently asked questions

How much does thinkingcap-qwen3.6-27b cost?
thinkingcap-qwen3.6-27b is priced at $0.40 per million input tokens and $3.00 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of thinkingcap-qwen3.6-27b?
thinkingcap-qwen3.6-27b has a context window of 262K tokens, with a maximum output of 33K tokens per response. That's roughly 350 words of input you can fit in a single prompt.
What can thinkingcap-qwen3.6-27b do?
thinkingcap-qwen3.6-27b supports tool calling, extended reasoning. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use thinkingcap-qwen3.6-27b with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "sference/thinkingcap-qwen3.6-27b". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run thinkingcap-qwen3.6-27b through Requesty?
Yes. thinkingcap-qwen3.6-27b runs through Requesty's OpenAI-compatible API, served from sference. You do not host the model yourself: point base_url at Requesty, set the model to "sference/thinkingcap-qwen3.6-27b", and requests are routed to the upstream provider with automatic failover. The same key gives you 400+ other models too.

Access thinkingcap-qwen3.6-27b through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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