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Gemini 3 Pro vs GLM-5.3-Flash

GLM-5.3-Flash significantly outperforms across most benchmarks. GLM-5.3-Flash is 18.9x cheaper per token.

Google · Zhipu AI · Updated for 2026

Which is better?

Gemini 3 Pro outperforms in 0 benchmarks, while GLM-5.3-Flash is better at 2 benchmarks (CharXiv-R, Humanity's Last Exam). GLM-5.3-Flash significantly outperforms across most benchmarks.

On price, GLM-5.3-Flash is roughly 18.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

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

Choose Gemini 3 Pro

  • you want predictable pricing at $2.00/M input and $12.00/M output

Choose GLM-5.3-Flash

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • cost matters — it's about 18.9x cheaper per token
  • you want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Benchmark wins
0 of 2
2 of 2
Input price
$2.00 / M
$0.15 / M
Output price
$12.00 / M
$0.50 / M
Context window
1,048,576
1,048,576
Released
Nov 2025
Aug 2026
License
Proprietary
MIT

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 3 Pro outperforms in 0 benchmarks, while GLM-5.3-Flash is better at 2 benchmarks (CharXiv-R, Humanity's Last Exam).

GLM-5.3-Flash significantly outperforms across most benchmarks.

Wed Aug 26 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

GLM-5.3-Flash costs less

For input processing, Gemini 3 Pro ($2.00/1M tokens) is 13.3x more expensive than GLM-5.3-Flash ($0.15/1M tokens).

For output processing, Gemini 3 Pro ($12.00/1M tokens) is 24.0x more expensive than GLM-5.3-Flash ($0.50/1M tokens).

In conclusion, Gemini 3 Pro is more expensive than GLM-5.3-Flash.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Aug 26 2026 • llm-stats.com
Google
Gemini 3 Pro
Input tokens$2.00
Output tokens$12.00
Best providerGoogle
Zhipu AI
GLM-5.3-Flash
Input tokens$0.15
Output tokens$0.50
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Gemini 3 Pro is limited to 65,536 tokens.

Google
Gemini 3 Pro
Input1,048,576 tokens
Output65,536 tokens
Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 3 Pro and GLM-5.3-Flash support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 3 Pro

Text
Images
Audio
Video

GLM-5.3-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3 Pro is licensed under a proprietary license, while GLM-5.3-Flash uses MIT.

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

Gemini 3 Pro

Proprietary

Closed source

GLM-5.3-Flash

MIT

Open weights

Release Timeline

When each model was launched

Gemini 3 Pro was released on 2025-11-18, while GLM-5.3-Flash was released on 2026-08-26.

GLM-5.3-Flash is 9 months newer than Gemini 3 Pro.

Gemini 3 Pro

Nov 18, 2025

9 months ago

GLM-5.3-Flash

Aug 26, 2026

0 days ago

9mo newer

Knowledge Cutoff

When training data ends

Gemini 3 Pro has a documented knowledge cutoff of 2025-01-31, while GLM-5.3-Flash's cutoff date is not specified.

We can confirm Gemini 3 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.

Gemini 3 Pro

Jan 2025

GLM-5.3-Flash

Provider Availability

Gemini 3 Pro is available from Google. GLM-5.3-Flash is available from DeepInfra, Novita, ZAI.

Gemini 3 Pro

google logo
Google
Input Price:Input: $2.00/1MOutput Price:Output: $12.00/1M

GLM-5.3-Flash

deepinfra logo
Deepinfra
Input Price:Input: $0.15/1MOutput Price:Output: $0.50/1M
novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $0.50/1M
z logo
Unknown Organization
Input Price:Input: $0.15/1MOutput Price:Output: $0.50/1M
* 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 Gemini 3 Pro and GLM-5.3-Flash side-by-side, then vote on the output you prefer.

Gemini 3 Pro
✓ Preferred
GLM-5.3-Flash
Open in Playground

FAQ

Common questions about Gemini 3 Pro vs GLM-5.3-Flash.

Which is better, Gemini 3 Pro or GLM-5.3-Flash?

GLM-5.3-Flash significantly outperforms across most benchmarks. Gemini 3 Pro is made by Google and GLM-5.3-Flash is made by Zhipu AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 3 Pro compare to GLM-5.3-Flash in benchmarks?

Gemini 3 Pro scores AIME 2025: 100.0%, Vending-Bench 2: 100.0%, Global PIQA: 93.4%, GPQA: 91.9%, MMMLU: 91.8%. GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%.

Is Gemini 3 Pro cheaper than GLM-5.3-Flash?

GLM-5.3-Flash is 13.3x cheaper for input tokens. Gemini 3 Pro costs $2.00/M input and $12.00/M output via google. GLM-5.3-Flash costs $0.15/M input and $0.50/M output via deepinfra.

What are the context window sizes for Gemini 3 Pro and GLM-5.3-Flash?

Gemini 3 Pro supports 1.0M tokens and GLM-5.3-Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 3 Pro and GLM-5.3-Flash?

Key differences include input pricing ($2.00 vs $0.15/M), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3 Pro and GLM-5.3-Flash?

Gemini 3 Pro is developed by Google and GLM-5.3-Flash is developed by Zhipu AI.