The AI arena is free today

Open Superagent

GLM-5 vs Qwen3.5-0.8B

GLM-5 leads the LLM Stats Score 37.1 to -5.9.

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

Which is better?

GLM-5 leads the overall LLM Stats Score 37.1 to -5.9, ranking #65 overall.

In the 1 individual benchmarks reported for both models, GLM-5 wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-5

  • overall performance matters — it scores 37.1 and ranks #65 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

Choose Qwen3.5-0.8B

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

At a glance

The differences that matter most.

Core performance indexes
37.1
#65
-5.9
#348
37.3
#63
-3.2
#323
19.2
#57
-9.6
#172
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$1.00 / M
— / M
Output price
$3.20 / M
— / M
Context window
200,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-5
Qwen3.5-0.8B
18.0#68
-9.5#183
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

5 reported for GLM-5 · 20 for Qwen3.5-0.8B

1 shared

GLM-5 outperforms in 1 benchmarks (t2-bench), while Qwen3.5-0.8B is better at 0 benchmarks.

GLM-5 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

743.2B diff

GLM-5 has 743.2B more parameters than Qwen3.5-0.8B, making it 92900.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.5-0.8B
800,000,000parameters
744.0B
GLM-5
0.8B
Qwen3.5-0.8B

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3.5-0.8B
Input- tokens
Output- tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.5-0.8B supports multimodal inputs, whereas GLM-5 does not.

Qwen3.5-0.8B can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Qwen3.5-0.8B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Qwen3.5-0.8B uses Apache 2.0.

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

GLM-5

MIT

Open weights

Qwen3.5-0.8B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Qwen3.5-0.8B was released on 2026-03-02.

Qwen3.5-0.8B is 1 month newer than GLM-5.

GLM-5

Feb 11, 2026

6 months ago

Qwen3.5-0.8B

Mar 2, 2026

6 months ago

2w 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GLM-5 and Qwen3.5-0.8B side-by-side, then vote on the output you prefer.

GLM-5
✓ Preferred
Qwen3.5-0.8B
Open in Playground

FAQ

Common questions about GLM-5 vs Qwen3.5-0.8B.

Which is better, GLM-5 or Qwen3.5-0.8B?

GLM-5 leads the LLM Stats Score 37.1 to -5.9. GLM-5 is made by Zhipu AI and Qwen3.5-0.8B 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 compare to Qwen3.5-0.8B in benchmarks?

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Qwen3.5-0.8B scores MMLU-Redux: 59.5%, Global PIQA: 59.4%, C-Eval: 50.5%, MMMLU: 44.3%, IFEval: 44.0%.

What are the context window sizes for GLM-5 and Qwen3.5-0.8B?

GLM-5 supports 200K tokens and Qwen3.5-0.8B supports an unknown number of 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 and Qwen3.5-0.8B?

Key differences include LLM Stats Score (37.1 vs -5.9), 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 and Qwen3.5-0.8B?

GLM-5 is developed by Zhipu AI and Qwen3.5-0.8B is developed by Alibaba Cloud / Qwen Team.