GPT-6 Astra vs Qwen3.6-27B
GPT-6 Astra leads the LLM Stats Score 60.4 to 35.7. Qwen3.6-27B is 14.8x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-6 Astra leads the overall LLM Stats Score 60.4 to 35.7, ranking #1 overall.
In the 1 individual benchmarks reported for both models, GPT-6 Astra wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.6-27B is roughly 14.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Astra also accepts a larger context window (1,050,000 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-6 Astra
- overall performance matters — it scores 60.4 and ranks #1 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Qwen3.6-27B
- cost matters — it's about 14.8x cheaper per token
- 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
22 reported for GPT-6 Astra · 44 for Qwen3.6-27B
GPT-6 Astra outperforms in 1 benchmarks (GPQA), while Qwen3.6-27B is better at 0 benchmarks.
GPT-6 Astra significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Astra ($10.00/1M tokens) is 16.7x more expensive than Qwen3.6-27B ($0.60/1M tokens).
For output processing, GPT-6 Astra ($50.00/1M tokens) is 13.9x more expensive than Qwen3.6-27B ($3.60/1M tokens).
In conclusion, GPT-6 Astra 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-6 Astra accepts 1,050,000 input tokens compared to Qwen3.6-27B's 262,144 tokens. GPT-6 Astra can generate longer responses up to 128,000 tokens, while Qwen3.6-27B is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-6 Astra and Qwen3.6-27B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6 Astra
Qwen3.6-27B
License
Usage and distribution terms
GPT-6 Astra 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-6 Astra was released on 2026-09-04, while Qwen3.6-27B was released on 2026-04-21.
GPT-6 Astra is 5 months newer than Qwen3.6-27B.
Sep 4, 2026
4 days ago
4mo newerApr 21, 2026
4 months ago
Knowledge Cutoff
When training data ends
GPT-6 Astra has a documented knowledge cutoff of 2026-04-30, while Qwen3.6-27B's cutoff date is not specified.
We can confirm GPT-6 Astra's training data extends to 2026-04-30, but cannot make a direct comparison without Qwen3.6-27B's cutoff date.
Apr 2026
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Provider Availability
GPT-6 Astra is available from OpenAI. Qwen3.6-27B is available from Novita.
GPT-6 Astra
Qwen3.6-27B
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Astra and Qwen3.6-27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Astra vs Qwen3.6-27B.