Model Comparison

Gemma 4 31B vs GLM-5V-TurboWhich is better in 2026?

Comparing Gemma 4 31B and GLM-5V-Turbo across benchmarks, pricing, and capabilities.

Verdict: Gemma 4 31B vs GLM-5V-Turbo — which is better?

Gemma 4 31B (by Google) and GLM-5V-Turbo (by Zhipu AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

On price, Gemma 4 31B is roughly 9.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemma 4 31B also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemma 4 31B if…

  • cost matters — it's about 9.9x cheaper per token
  • you process long inputs — it offers a 262,144 token context window
  • you need open weights you can self-host or fine-tune

Choose GLM-5V-Turbo if…

  • you want predictable pricing at $1.20/M input and $4.00/M output

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 4 31B and GLM-5V-Turbodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 4 31B costs less

For input processing, Gemma 4 31B ($0.13/1M tokens) is 9.2x cheaper than GLM-5V-Turbo ($1.20/1M tokens).

For output processing, Gemma 4 31B ($0.38/1M tokens) is 10.5x cheaper than GLM-5V-Turbo ($4.00/1M tokens).

In conclusion, GLM-5V-Turbo is more expensive than Gemma 4 31B.*

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

Lowest available price from all providers
Fri Jul 17 2026 • llm-stats.com
Google
Gemma 4 31B
Input tokens$0.13
Output tokens$0.38
Best providerDeepinfra
Zhipu AI
GLM-5V-Turbo
Input tokens$1.20
Output tokens$4.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Gemma 4 31B accepts 262,144 input tokens compared to GLM-5V-Turbo's 200,000 tokens. Gemma 4 31B can generate longer responses up to 131,072 tokens, while GLM-5V-Turbo is limited to 128,000 tokens.

Google
Gemma 4 31B
Input262,144 tokens
Output131,072 tokens
Zhipu AI
GLM-5V-Turbo
Input200,000 tokens
Output128,000 tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 4 31B and GLM-5V-Turbo support multimodal inputs.

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

Gemma 4 31B

Text
Images
Audio
Video

GLM-5V-Turbo

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 4 31B is licensed under Apache 2.0, while GLM-5V-Turbo uses a proprietary license.

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

Gemma 4 31B

Apache 2.0

Open weights

GLM-5V-Turbo

Proprietary

Closed source

Release Timeline

When each model was launched

Both models were released on 2026-04-02.

They likely represent similar generations of model development.

Gemma 4 31B

Apr 2, 2026

3 months ago

GLM-5V-Turbo

Apr 2, 2026

3 months ago

Knowledge Cutoff

When training data ends

Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while GLM-5V-Turbo's cutoff date is not specified.

We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without GLM-5V-Turbo's cutoff date.

Gemma 4 31B

Jan 2025

GLM-5V-Turbo

Provider Availability

Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. GLM-5V-Turbo is available from ZAI.

Gemma 4 31B

deepinfra logo
Deepinfra
Input Price:Input: $0.13/1MOutput Price:Output: $0.38/1M
friendli logo
FriendliAI
Input Price:Input: $0.14/1MOutput Price:Output: $0.40/1M
novita logo
Novita
Input Price:Input: $0.14/1MOutput Price:Output: $0.40/1M
together logo
Together
Input Price:Input: $0.39/1MOutput Price:Output: $0.97/1M

GLM-5V-Turbo

z logo
Unknown Organization
Input Price:Input: $1.20/1MOutput Price:Output: $4.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (262,144 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights

No standout differentiators in the data we have for this pair.

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemma 4 31B and GLM-5V-Turbo side-by-side, then vote on the output you prefer.

Gemma 4 31B
✓ Preferred
GLM-5V-Turbo
Open in Playground
AI Model Comparison Table
Feature
Google
Gemma 4 31B
Zhipu AI
GLM-5V-Turbo

FAQ

Common questions about Gemma 4 31B vs GLM-5V-Turbo.

Which is better, Gemma 4 31B or GLM-5V-Turbo?

Gemma 4 31B (Google) and GLM-5V-Turbo (Zhipu AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemma 4 31B compare to GLM-5V-Turbo in benchmarks?

Gemma 4 31B scores AIME 2026: 89.2%, MMMLU: 88.4%, t2-bench: 86.4%, MathVision: 85.6%, MMLU-Pro: 85.2%. GLM-5V-Turbo scores Design2Code: 94.8%, Flame-VLM-Code: 93.8%, V*: 89.0%, WebVoyager: 88.5%, PinchBench: 80.7%.

Is Gemma 4 31B cheaper than GLM-5V-Turbo?

Gemma 4 31B is 9.2x cheaper for input tokens. Gemma 4 31B costs $0.13/M input and $0.38/M output via deepinfra. GLM-5V-Turbo costs $1.20/M input and $4.00/M output via z.

What are the context window sizes for Gemma 4 31B and GLM-5V-Turbo?

Gemma 4 31B supports 262K tokens and GLM-5V-Turbo supports 200K 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 31B and GLM-5V-Turbo?

Key differences include context window (262K vs 200K), input pricing ($0.13 vs $1.20/M), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 4 31B and GLM-5V-Turbo?

Gemma 4 31B is developed by Google and GLM-5V-Turbo is developed by Zhipu AI.