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Gemini 2.5 Flash-Lite vs GLM-5.3

GLM-5.3 significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite is 12.3x cheaper per token.

Google · Zhipu AI · Updated for 2026

Which is better?

Gemini 2.5 Flash-Lite outperforms in 0 benchmarks, while GLM-5.3 is better at 1 benchmark (Humanity's Last Exam). GLM-5.3 significantly outperforms across most benchmarks.

On price, Gemini 2.5 Flash-Lite is roughly 12.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 2.5 Flash-Lite 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 benchmark, pricing, and model metadata for 2026.

Choose Gemini 2.5 Flash-Lite

  • cost matters — it's about 12.3x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you need open weights you can self-host or fine-tune

Choose GLM-5.3

  • 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

At a glance

The differences that matter most.

Gemini 2.5 Flash-Lite
Google
GLM-5.3
Zhipu AI
Benchmark wins
0 of 1
1 of 1
Input price
$0.10 / M
$1.40 / M
Output price
$0.40 / M
$4.40 / M
Context window
1,048,576
1,000,000
Released
Jun 2025
Aug 2026
License
Creative Commons Attribution 4.0 License
Unknown

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemini 2.5 Flash-Lite outperforms in 0 benchmarks, while GLM-5.3 is better at 1 benchmark (Humanity's Last Exam).

GLM-5.3 significantly outperforms across most benchmarks.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

Gemini 2.5 Flash-Lite costs less

For input processing, Gemini 2.5 Flash-Lite ($0.10/1M tokens) is 14.0x cheaper than GLM-5.3 ($1.40/1M tokens).

For output processing, Gemini 2.5 Flash-Lite ($0.40/1M tokens) is 11.0x cheaper than GLM-5.3 ($4.40/1M tokens).

In conclusion, GLM-5.3 is more expensive than Gemini 2.5 Flash-Lite.*

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

Lowest available price from all providers
Tue Aug 25 2026 • llm-stats.com
Google
Gemini 2.5 Flash-Lite
Input tokens$0.10
Output tokens$0.40
Best providerGoogle
Zhipu AI
GLM-5.3
Input tokens$1.40
Output tokens$4.40
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 2.5 Flash-Lite accepts 1,048,576 input tokens compared to GLM-5.3's 1,000,000 tokens. GLM-5.3 can generate longer responses up to 128,000 tokens, while Gemini 2.5 Flash-Lite is limited to 65,536 tokens.

Google
Gemini 2.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
Zhipu AI
GLM-5.3
Input1,000,000 tokens
Output128,000 tokens
Tue Aug 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.5 Flash-Lite supports multimodal inputs, whereas GLM-5.3 does not.

Gemini 2.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 2.5 Flash-Lite

Text
Images
Audio
Video

GLM-5.3

Text
Images
Audio
Video

Release Timeline

When each model was launched

Gemini 2.5 Flash-Lite was released on 2025-06-17, while GLM-5.3 was released on 2026-08-14.

GLM-5.3 is 14 months newer than Gemini 2.5 Flash-Lite.

Gemini 2.5 Flash-Lite

Jun 17, 2025

1.2 years ago

GLM-5.3

Aug 14, 2026

1 weeks ago

1.2yr newer

Knowledge Cutoff

When training data ends

Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while GLM-5.3's cutoff date is not specified.

We can confirm Gemini 2.5 Flash-Lite's training data extends to 2025-01-01, but cannot make a direct comparison without GLM-5.3's cutoff date.

Gemini 2.5 Flash-Lite

Jan 2025

GLM-5.3

—

Provider Availability

Gemini 2.5 Flash-Lite is available from Google. GLM-5.3 is available from ZAI.

Gemini 2.5 Flash-Lite

google logo
Google
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

GLM-5.3

z logo
Unknown Organization
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
* 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 2.5 Flash-Lite and GLM-5.3 side-by-side, then vote on the output you prefer.

Gemini 2.5 Flash-Lite
✓ Preferred
GLM-5.3
Open in Playground

FAQ

Common questions about Gemini 2.5 Flash-Lite vs GLM-5.3.

Which is better, Gemini 2.5 Flash-Lite or GLM-5.3?

GLM-5.3 significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite is made by Google and GLM-5.3 is made by Zhipu AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 2.5 Flash-Lite compare to GLM-5.3 in benchmarks?

Gemini 2.5 Flash-Lite scores FACTS Grounding: 84.1%, Global-MMLU-Lite: 81.1%, MMMU: 72.9%, GPQA: 64.6%, Vibe-Eval: 51.3%. GLM-5.3 scores Terminal-Bench 2.1: 88.2%, CyberGym: 84.5%, FrontierSWE: 78.1%, Toolathlon: 73.0%, DeepSWE 1.1: 66.9%.

Is Gemini 2.5 Flash-Lite cheaper than GLM-5.3?

Gemini 2.5 Flash-Lite is 14.0x cheaper for input tokens. Gemini 2.5 Flash-Lite costs $0.10/M input and $0.40/M output via google. GLM-5.3 costs $1.40/M input and $4.40/M output via z.

What are the context window sizes for Gemini 2.5 Flash-Lite and GLM-5.3?

Gemini 2.5 Flash-Lite supports 1.0M tokens and GLM-5.3 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 2.5 Flash-Lite and GLM-5.3?

Key differences include context window (1.0M vs 1.0M), input pricing ($0.10 vs $1.40/M), multimodal support (yes vs no), licensing (Creative Commons Attribution 4.0 License vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.5 Flash-Lite and GLM-5.3?

Gemini 2.5 Flash-Lite is developed by Google and GLM-5.3 is developed by Zhipu AI.

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