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GLM-5.3-Flash vs Kimi K2-Instruct-0905

GLM-5.3-Flash significantly outperforms across most benchmarks.

Zhipu AI · Moonshot AI · Updated for 2026

Which is better?

GLM-5.3-Flash outperforms in 1 benchmarks (Humanity's Last Exam), while Kimi K2-Instruct-0905 is better at 0 benchmarks. GLM-5.3-Flash significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose GLM-5.3-Flash

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

Choose Kimi K2-Instruct-0905

  • you are already invested in the Moonshot AI ecosystem

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
Kimi K2-Instruct-0905
Moonshot AI
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
—
Released
Aug 2026
Sep 2025
License
MIT
MIT

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-5.3-Flash outperforms in 1 benchmarks (Humanity's Last Exam), while Kimi K2-Instruct-0905 is better at 0 benchmarks.

GLM-5.3-Flash significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

680.0B diff

Kimi K2-Instruct-0905 has 680.0B more parameters than GLM-5.3-Flash, making it 212.5% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Moonshot AI
Kimi K2-Instruct-0905
1.0Tparameters
320.0B
GLM-5.3-Flash
1000.0B
Kimi K2-Instruct-0905

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
Moonshot AI
Kimi K2-Instruct-0905
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-5.3-Flash supports multimodal inputs, whereas Kimi K2-Instruct-0905 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

Kimi K2-Instruct-0905

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

GLM-5.3-Flash

MIT

Open weights

Kimi K2-Instruct-0905

MIT

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Kimi K2-Instruct-0905 was released on 2025-09-05.

GLM-5.3-Flash is 12 months newer than Kimi K2-Instruct-0905.

GLM-5.3-Flash

Aug 26, 2026

2 days ago

11mo newer
Kimi K2-Instruct-0905

Sep 5, 2025

11 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 Kimi K2-Instruct-0905 side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Kimi K2-Instruct-0905
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Kimi K2-Instruct-0905.

Which is better, GLM-5.3-Flash or Kimi K2-Instruct-0905?

GLM-5.3-Flash significantly outperforms across most benchmarks. GLM-5.3-Flash is made by Zhipu AI and Kimi K2-Instruct-0905 is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GLM-5.3-Flash compare to Kimi K2-Instruct-0905 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%. Kimi K2-Instruct-0905 scores MATH-500: 97.4%, MMLU-Redux: 92.7%, IFEval: 89.8%, AutoLogi: 89.5%, MMLU: 89.5%.

What are the context window sizes for GLM-5.3-Flash and Kimi K2-Instruct-0905?

GLM-5.3-Flash supports 1.0M tokens and Kimi K2-Instruct-0905 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 Kimi K2-Instruct-0905?

Key differences include multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and Kimi K2-Instruct-0905?

GLM-5.3-Flash is developed by Zhipu AI and Kimi K2-Instruct-0905 is developed by Moonshot AI.

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