Gemma 4 26B-A4B vs GLM-4.6
Gemma 4 26B-A4B and GLM-4.6 are closely matched at 29.6 and 29.0 on the LLM Stats Score. Gemma 4 26B-A4B is 6.4x cheaper per token.
Google · Zhipu AI · Updated for 2026
Which is better?
Gemma 4 26B-A4B and GLM-4.6 are closely matched on the overall LLM Stats Score at 29.6 and 29.0.
In the 3 individual benchmarks reported for both models, GLM-4.6 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 4 26B-A4B is roughly 6.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemma 4 26B-A4B also accepts a larger context window (262,144 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 6.4x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Apr 2026
Choose GLM-4.6
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for Gemma 4 26B-A4B · 7 for GLM-4.6
Gemma 4 26B-A4B outperforms in 1 benchmarks (GPQA), while GLM-4.6 is better at 1 benchmark (LiveCodeBench v6).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 4 26B-A4B ($0.07/1M tokens) is 7.1x cheaper than GLM-4.6 ($0.50/1M tokens).
For output processing, Gemma 4 26B-A4B ($0.34/1M tokens) is 5.9x cheaper than GLM-4.6 ($2.00/1M tokens).
In conclusion, GLM-4.6 is more expensive than Gemma 4 26B-A4B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-4.6 has 331.8B more parameters than Gemma 4 26B-A4B, making it 1316.7% larger.
Context Window
Maximum input and output token capacity
Gemma 4 26B-A4B accepts 262,144 input tokens compared to GLM-4.6's 202,752 tokens. Gemma 4 26B-A4B can generate longer responses up to 262,144 tokens, while GLM-4.6 is limited to 202,752 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 4 26B-A4B and GLM-4.6 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 4 26B-A4B
GLM-4.6
License
Usage and distribution terms
Gemma 4 26B-A4B is licensed under Apache 2.0, while GLM-4.6 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Gemma 4 26B-A4B was released on 2026-04-02, while GLM-4.6 was released on 2025-09-30.
Gemma 4 26B-A4B is 6 months newer than GLM-4.6.
Apr 2, 2026
5 months ago
6mo newerSep 30, 2025
11 months ago
Knowledge Cutoff
When training data ends
Gemma 4 26B-A4B has a documented knowledge cutoff of 2025-01-01, while GLM-4.6'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-4.6's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 26B-A4B is available from DeepInfra, Novita. GLM-4.6 is available from DeepInfra, Fireworks.
Gemma 4 26B-A4B
GLM-4.6
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 4 26B-A4B and GLM-4.6 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 4 26B-A4B vs GLM-4.6.