Inkling vs Qwen3.6-27B
Inkling and Qwen3.6-27B are closely matched at 37.5 and 35.6 on the LLM Stats Score. Qwen3.6-27B is 1.7x cheaper per token.
Thinking Machines Lab · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Inkling and Qwen3.6-27B are closely matched on the overall LLM Stats Score at 37.5 and 35.6.
The models split the 4 individual benchmarks reported for both models evenly.
On price, Qwen3.6-27B is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Inkling also accepts a larger context window (524,288 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Inkling
- you process long inputs — it offers a 524,288 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Qwen3.6-27B
- cost matters — it's about 1.7x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for Inkling · 44 for Qwen3.6-27B
Inkling outperforms in 2 benchmarks (AIME 2026, SWE-Bench Verified), while Qwen3.6-27B is better at 2 benchmarks (CharXiv-R, MMMU-Pro).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Inkling ($0.95/1M tokens) is 3.0x more expensive than Qwen3.6-27B ($0.32/1M tokens).
For output processing, Inkling ($4.05/1M tokens) is 1.3x more expensive than Qwen3.6-27B ($3.20/1M tokens).
In conclusion, Inkling is more expensive than Qwen3.6-27B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Inkling has 947.2B more parameters than Qwen3.6-27B, making it 3409.5% larger.
Context Window
Maximum input and output token capacity
Inkling accepts 524,288 input tokens compared to Qwen3.6-27B's 262,144 tokens. Inkling can generate longer responses up to 524,288 tokens, while Qwen3.6-27B is limited to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
Both Inkling and Qwen3.6-27B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Inkling
Qwen3.6-27B
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Inkling was released on 2026-07-21, while Qwen3.6-27B was released on 2026-04-21.
Inkling is 3 months newer than Qwen3.6-27B.
Jul 21, 2026
1 months ago
3mo newerApr 21, 2026
4 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Inkling is available from DeepInfra. Qwen3.6-27B is available from DeepInfra, Novita.
Inkling
Qwen3.6-27B
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling and Qwen3.6-27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling vs Qwen3.6-27B.