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GLM-5.3-Flash vs MAI-Code-1-Flash

GLM-5.3-Flash leads the LLM Stats Score 50.7 to 29.3.

Zhipu AI · Microsoft · Updated for 2026

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 50.7 to 29.3, ranking #16 overall.

In the 1 individual benchmarks reported for both models, GLM-5.3-Flash 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-5.3-Flash

  • overall performance matters — it scores 50.7 and ranks #16 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 want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

Choose MAI-Code-1-Flash

  • you are already invested in the Microsoft ecosystem

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
MAI-Code-1-Flash
Microsoft
Core performance indexes
LLM Stats Score
50.7
#16
29.3
#122
Reasoning
49.5
#15
29.0
#115
Coding
34.6
#30
19.8
#96
Agents
37.0
#13
10.9
#101
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-5.3-Flash
MAI-Code-1-Flash
Tool use
32.2#5
10.6#119
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for GLM-5.3-Flash · 15 for MAI-Code-1-Flash

1 shared

GLM-5.3-Flash outperforms in 1 benchmarks (Humanity's Last Exam), while MAI-Code-1-Flash is better at 0 benchmarks.

GLM-5.3-Flash significantly outperforms across most benchmarks.

Sat Sep 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Microsoft
MAI-Code-1-Flash
Input- tokens
Output- tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GLM-5.3-Flash supports multimodal inputs, whereas MAI-Code-1-Flash does not.

GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5.3-Flash

Text
Images
Audio
Video

MAI-Code-1-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, while MAI-Code-1-Flash uses a proprietary license.

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

GLM-5.3-Flash

MIT

Open weights

MAI-Code-1-Flash

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while MAI-Code-1-Flash was released on 2026-06-02.

GLM-5.3-Flash is 3 months newer than MAI-Code-1-Flash.

GLM-5.3-Flash

Aug 26, 2026

1 weeks ago

2mo newer
MAI-Code-1-Flash

Jun 2, 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.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-5.3-Flash and MAI-Code-1-Flash side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
MAI-Code-1-Flash
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs MAI-Code-1-Flash.

Which is better, GLM-5.3-Flash or MAI-Code-1-Flash?

GLM-5.3-Flash leads the LLM Stats Score 50.7 to 29.3. GLM-5.3-Flash is made by Zhipu AI and MAI-Code-1-Flash is made by Microsoft. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-5.3-Flash compare to MAI-Code-1-Flash in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. MAI-Code-1-Flash scores AIME 2026: 92.5%, GPQA: 84.6%, IFBench: 75.0%, Tau2 Telecom: 71.7%, SWE-Bench Verified: 71.6%.

What are the context window sizes for GLM-5.3-Flash and MAI-Code-1-Flash?

GLM-5.3-Flash supports 1.0M tokens and MAI-Code-1-Flash 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-5.3-Flash and MAI-Code-1-Flash?

Key differences include LLM Stats Score (50.7 vs 29.3), multimodal support (yes vs no), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and MAI-Code-1-Flash?

GLM-5.3-Flash is developed by Zhipu AI and MAI-Code-1-Flash is developed by Microsoft.

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