GPT-5 vs Qwen3.6-27B
GPT-5 and Qwen3.6-27B are closely matched at 33.8 and 35.5 on the LLM Stats Score. Qwen3.6-27B is 3.3x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5 and Qwen3.6-27B are closely matched on the overall LLM Stats Score at 33.8 and 35.5.
In the 10 individual benchmarks reported for both models, GPT-5 wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.6-27B is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5 also accepts a larger context window (400,000 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 GPT-5
- you value its reported benchmark strengths — it wins 6 of 10 exact shared results
- you process long inputs — it offers a 400,000 token context window
Choose Qwen3.6-27B
- cost matters — it's about 3.3x cheaper per token
- you want the most recent training data — it shipped Apr 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
34 reported for GPT-5 · 44 for Qwen3.6-27B
GPT-5 outperforms in 6 benchmarks (CharXiv-R, ERQA, Humanity's Last Exam, MMMU, MMMU-Pro, VideoMMMU), while Qwen3.6-27B is better at 4 benchmarks (GPQA, HMMT 2025, SWE-Bench Verified, VideoMME w sub.).
GPT-5 has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5 ($1.25/1M tokens) is 3.9x more expensive than Qwen3.6-27B ($0.32/1M tokens).
For output processing, GPT-5 ($10.00/1M tokens) is 3.1x more expensive than Qwen3.6-27B ($3.20/1M tokens).
In conclusion, GPT-5 is more expensive than Qwen3.6-27B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5 accepts 400,000 input tokens compared to Qwen3.6-27B's 262,144 tokens. Qwen3.6-27B can generate longer responses up to 262,144 tokens, while GPT-5 is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5 and Qwen3.6-27B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5
Qwen3.6-27B
License
Usage and distribution terms
GPT-5 is licensed under a proprietary license, while Qwen3.6-27B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-5 was released on 2025-08-07, while Qwen3.6-27B was released on 2026-04-21.
Qwen3.6-27B is 9 months newer than GPT-5.
Aug 7, 2025
1.1 years ago
Apr 21, 2026
5 months ago
8mo newerKnowledge Cutoff
When training data ends
GPT-5 has a documented knowledge cutoff of 2024-09-30, while Qwen3.6-27B's cutoff date is not specified.
We can confirm GPT-5's training data extends to 2024-09-30, but cannot make a direct comparison without Qwen3.6-27B's cutoff date.
Sep 2024
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Provider Availability
GPT-5 is available from OpenAI. Qwen3.6-27B is available from DeepInfra, Novita.
GPT-5
Qwen3.6-27B
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 and Qwen3.6-27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 vs Qwen3.6-27B.