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GLM-5.2 vs Qwen3.8-27B

GLM-5.2 and Qwen3.8-27B are closely matched at 45.7 and 45.2 on the LLM Stats Score.

Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

GLM-5.2 and Qwen3.8-27B are closely matched on the overall LLM Stats Score at 45.7 and 45.2.

In the 6 individual benchmarks reported for both models, GLM-5.2 wins 6; this is a narrower head-to-head signal than the composite indexes.

GLM-5.2 also accepts a larger context window (1,048,576 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 GLM-5.2

  • you value its reported benchmark strengths — it wins 6 of 6 exact shared results
  • you process long inputs — it offers a 1,048,576 token context window

Choose Qwen3.8-27B

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Core performance indexes
45.7
#26
45.2
#30
45.0
#29
44.8
#30
35.3
#26
31.6
#39
29.7
#32
30.4
#31
Cost, coverage & limits
Benchmark wins
6 of 6
0 of 6
Input price
$0.95 / M
— / M
Output price
$3.00 / M
— / M
Context window
1,048,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
GLM-5.2
Qwen3.8-27B
41.3#7
31.0#68
22.0#46
22.7#42
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for GLM-5.2 · 26 for Qwen3.8-27B

6 shared

GLM-5.2 outperforms in 6 benchmarks (DeepSWE 1.1, GPQA, Humanity's Last Exam, NL2Repo, SWE-Bench Pro, Terminal-Bench 2.1), while Qwen3.8-27B is better at 0 benchmarks.

GLM-5.2 significantly outperforms across most benchmarks.

Sat Sep 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

725.2B diff

GLM-5.2 has 725.2B more parameters than Qwen3.8-27B, making it 2610.4% larger.

Zhipu AI
GLM-5.2
753.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
753.0B
GLM-5.2
27.8B
Qwen3.8-27B

Context Window

Maximum input and output token capacity

GLM-5.2 accepts 1,048,576 input tokens compared to Qwen3.8-27B's 262,144 tokens. Both models can generate responses up to 131,072 tokens.

Zhipu AI
GLM-5.2
Input1,048,576 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input262,144 tokens
Output131,072 tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8-27B supports multimodal inputs, whereas GLM-5.2 does not.

Qwen3.8-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5.2

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.2 is licensed under MIT, while Qwen3.8-27B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-5.2

MIT

Open weights

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5.2 was released on 2026-06-16, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 2 months newer than GLM-5.2.

GLM-5.2

Jun 16, 2026

2 months ago

Qwen3.8-27B

Aug 14, 2026

3 weeks ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. Qwen3.8-27B is available from FriendliAI.

GLM-5.2

deepinfra logo
Deepinfra
Input Price:Input: $0.95/1MOutput Price:Output: $3.00/1M
fireworks logo
Fireworks
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
friendli logo
FriendliAI
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
novita logo
Novita
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
together logo
Together
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
z logo
Unknown Organization
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M

Qwen3.8-27B

friendli logo
FriendliAI
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GLM-5.2 and Qwen3.8-27B side-by-side, then vote on the output you prefer.

GLM-5.2
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about GLM-5.2 vs Qwen3.8-27B.

Which is better, GLM-5.2 or Qwen3.8-27B?

GLM-5.2 and Qwen3.8-27B are closely matched on the LLM Stats Score at 45.7 and 45.2. GLM-5.2 is made by Zhipu AI and Qwen3.8-27B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-5.2 compare to Qwen3.8-27B in benchmarks?

GLM-5.2 scores AIME 2026: 99.2%, HMMT 2025: 94.4%, HMMT Feb 26: 92.5%, GPQA: 91.2%, IMO-AnswerBench: 91.0%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the context window sizes for GLM-5.2 and Qwen3.8-27B?

GLM-5.2 supports 1.0M tokens and Qwen3.8-27B supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5.2 and Qwen3.8-27B?

Key differences include LLM Stats Score (45.7 vs 45.2), context window (1.0M vs 262K), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.2 and Qwen3.8-27B?

GLM-5.2 is developed by Zhipu AI and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.