Model Comparison
Qwen3.6-27B vs GLM-5.1Which is better in 2026?
GLM-5.1 significantly outperforms across most benchmarks. Qwen3.6-27B is 1.6x cheaper per token.
Verdict: Qwen3.6-27B vs GLM-5.1 — which is better?
Qwen3.6-27B (by Alibaba Cloud / Qwen Team) and GLM-5.1 (by Zhipu AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Qwen3.6-27B outperforms in 2 benchmarks (GPQA, HMMT Feb 26), while GLM-5.1 is better at 8 benchmarks (AIME 2026, GDPval-AA, HMMT 2025, Humanity's Last Exam, IMO-AnswerBench, NL2Repo, SWE-Bench Pro, Terminal-Bench 2.0). GLM-5.1 significantly outperforms across most benchmarks.
On price, Qwen3.6-27B is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.6-27B also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose Qwen3.6-27B if…
- cost matters — it's about 1.6x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Apr 2026
Choose GLM-5.1 if…
- you want the strongest raw capability — it leads on 8 of 10 shared benchmarks
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.6-27B outperforms in 2 benchmarks (GPQA, HMMT Feb 26), while GLM-5.1 is better at 8 benchmarks (AIME 2026, GDPval-AA, HMMT 2025, Humanity's Last Exam, IMO-AnswerBench, NL2Repo, SWE-Bench Pro, Terminal-Bench 2.0).
GLM-5.1 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3.6-27B ($0.60/1M tokens) is 2.3x cheaper than GLM-5.1 ($1.40/1M tokens).
For output processing, Qwen3.6-27B ($3.60/1M tokens) is 1.2x cheaper than GLM-5.1 ($4.40/1M tokens).
In conclusion, GLM-5.1 is more expensive than Qwen3.6-27B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.1 has 726.2B more parameters than Qwen3.6-27B, making it 2614.0% larger.
Context Window
Maximum input and output token capacity
Qwen3.6-27B accepts 262,144 input tokens compared to GLM-5.1's 200,000 tokens. GLM-5.1 can generate longer responses up to 128,000 tokens, while Qwen3.6-27B is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Qwen3.6-27B supports multimodal inputs, whereas GLM-5.1 does not.
Qwen3.6-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3.6-27B
GLM-5.1
License
Usage and distribution terms
Qwen3.6-27B is licensed under Apache 2.0, while GLM-5.1 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Qwen3.6-27B was released on 2026-04-21, while GLM-5.1 was released on 2026-04-07.
Qwen3.6-27B is 0 month newer than GLM-5.1.
Apr 21, 2026
2 months ago
2w newerApr 7, 2026
3 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
Qwen3.6-27B is available from Novita. GLM-5.1 is available from FriendliAI, ZAI.
Qwen3.6-27B
GLM-5.1
Outputs Comparison
Key Takeaways
Qwen3.6-27B
View detailsAlibaba Cloud / Qwen Team
GLM-5.1
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Qwen3.6-27B and GLM-5.1 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Qwen3.6-27B vs GLM-5.1.