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Gemma 4 26B-A4B vs GLM-5.3-Flash

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 29.6. Gemma 4 26B-A4B is 1.2x cheaper per token.

Google · Zhipu AI · Updated for 2026

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to 29.6, ranking #11 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.

On price, Gemma 4 26B-A4B is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5.3-Flash 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemma 4 26B-A4B

  • cost matters — it's about 1.2x cheaper per token

Choose GLM-5.3-Flash

  • overall performance matters — it scores 51.6 and ranks #11 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
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Gemma 4 26B-A4B
Google
GLM-5.3-Flash
Zhipu AI
Core performance indexes
LLM Stats Score
29.6
#112
51.6
#11
Reasoning
29.5
#106
50.3
#13
Agents
13.3
#88
39.1
#9
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.13 / M
$0.15 / M
Output price
$0.40 / M
$0.50 / M
Context window
262,144
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemma 4 26B-A4B
GLM-5.3-Flash
Vision
14.3#86
32.0#21
Multimodal
17.9#67
30.9#24
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for Gemma 4 26B-A4B · 15 for GLM-5.3-Flash

1 shared

Gemma 4 26B-A4B outperforms in 0 benchmarks, while GLM-5.3-Flash is better at 1 benchmark (Humanity's Last Exam).

GLM-5.3-Flash significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Gemma 4 26B-A4B costs less

For input processing, Gemma 4 26B-A4B ($0.13/1M tokens) is 1.2x cheaper than GLM-5.3-Flash ($0.15/1M tokens).

For output processing, Gemma 4 26B-A4B ($0.40/1M tokens) is 1.3x cheaper than GLM-5.3-Flash ($0.50/1M tokens).

In conclusion, GLM-5.3-Flash is more expensive than Gemma 4 26B-A4B.*

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

Lowest available price from all providers
Fri Aug 28 2026 • llm-stats.com
Google
Gemma 4 26B-A4B
Input tokens$0.13
Output tokens$0.40
Best providerNovita
Zhipu AI
GLM-5.3-Flash
Input tokens$0.15
Output tokens$0.50
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

294.8B diff

GLM-5.3-Flash has 294.8B more parameters than Gemma 4 26B-A4B, making it 1169.8% larger.

Google
Gemma 4 26B-A4B
25.2Bparameters
Zhipu AI
GLM-5.3-Flash
320.0Bparameters
25.2B
Gemma 4 26B-A4B
320.0B
GLM-5.3-Flash

Context Window

Maximum input and output token capacity

GLM-5.3-Flash accepts 1,048,576 input tokens compared to Gemma 4 26B-A4B's 262,144 tokens. Both models can generate responses up to 131,072 tokens.

Google
Gemma 4 26B-A4B
Input262,144 tokens
Output131,072 tokens
Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemma 4 26B-A4B and GLM-5.3-Flash support multimodal inputs.

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

Gemma 4 26B-A4B

Text
Images
Audio
Video

GLM-5.3-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 4 26B-A4B is licensed under Apache 2.0, while GLM-5.3-Flash uses MIT.

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

Gemma 4 26B-A4B

Apache 2.0

Open weights

GLM-5.3-Flash

MIT

Open weights

Release Timeline

When each model was launched

Gemma 4 26B-A4B was released on 2026-04-02, while GLM-5.3-Flash was released on 2026-08-26.

GLM-5.3-Flash is 5 months newer than Gemma 4 26B-A4B.

Gemma 4 26B-A4B

Apr 2, 2026

4 months ago

GLM-5.3-Flash

Aug 26, 2026

2 days ago

4mo newer

Knowledge Cutoff

When training data ends

Gemma 4 26B-A4B has a documented knowledge cutoff of 2025-01-01, while GLM-5.3-Flash's cutoff date is not specified.

We can confirm Gemma 4 26B-A4B's training data extends to 2025-01-01, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.

Gemma 4 26B-A4B

Jan 2025

GLM-5.3-Flash

—

Provider Availability

Gemma 4 26B-A4B is available from Novita. GLM-5.3-Flash is available from DeepInfra, Novita, ZAI.

Gemma 4 26B-A4B

novita logo
Novita
Input Price:Input: $0.13/1MOutput Price:Output: $0.40/1M

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 Gemma 4 26B-A4B and GLM-5.3-Flash side-by-side, then vote on the output you prefer.

Gemma 4 26B-A4B
✓ Preferred
GLM-5.3-Flash
Open in Playground

FAQ

Common questions about Gemma 4 26B-A4B vs GLM-5.3-Flash.

Which is better, Gemma 4 26B-A4B or GLM-5.3-Flash?

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 29.6. Gemma 4 26B-A4B is made by Google and GLM-5.3-Flash is made by Zhipu AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemma 4 26B-A4B compare to GLM-5.3-Flash in benchmarks?

Gemma 4 26B-A4B scores AIME 2026: 88.3%, MMMLU: 86.3%, t2-bench: 85.5%, MMLU-Pro: 82.6%, MathVision: 82.4%. 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 Gemma 4 26B-A4B cheaper than GLM-5.3-Flash?

Gemma 4 26B-A4B is 1.2x cheaper for input tokens. Gemma 4 26B-A4B costs $0.13/M input and $0.40/M output via novita. GLM-5.3-Flash costs $0.15/M input and $0.50/M output via deepinfra.

What are the context window sizes for Gemma 4 26B-A4B and GLM-5.3-Flash?

Gemma 4 26B-A4B supports 262K 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 Gemma 4 26B-A4B and GLM-5.3-Flash?

Key differences include LLM Stats Score (29.6 vs 51.6), context window (262K vs 1.0M), input pricing ($0.13 vs $0.15/M), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 4 26B-A4B and GLM-5.3-Flash?

Gemma 4 26B-A4B is developed by Google and GLM-5.3-Flash is developed by Zhipu AI.

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