Head to Head

google/gemma-4-31B-it vs zai-org/GLM-5.1

Pricing, experience, and what the community actually says.

★ Our Pick

google/gemma-4-31B-it

google/gemma-4-31B-it

Starting at

0.00 (Self-hosted)

Refund

N/A (Open-source model)

Try Free →
zai-org/GLM-5.1

zai-org/GLM-5.1

Starting at

$1.40 / 1M input tokens

Refund

Pay-as-you-go model; no refunds on consumed tokens. Unused credits may expire per provider terms.

Try Free →

Our Take

google/gemma-4-31B-itgoogle/gemma-4-31B-it

“Yes, particularly for teams that prioritize open-weight licensing, local deployment, and transparent benchmarking over managed API convenience.”

Gemma 4 31B-it delivers strong reasoning and coding performance for its size, backed by an open Apache 2.0 license and broad ecosystem support. It is a practical choice for developers seeking a capable, locally deployable model without proprietary restrictions.

zai-org/GLM-5.1zai-org/GLM-5.1

“Worth it for developers and enterprises needing a highly capable, commercially permissive model for software engineering and complex multi-step agents, provided latency and token costs fit the budget.”

GLM-5.1 delivers frontier-level reasoning and coding performance under an open MIT license, but its high token cost and slower inference speed make it best suited for specialized, high-value tasks rather than high-volume, low-latency applications.

Pros & Cons

google/gemma-4-31B-it

✓Strong reasoning and coding benchmarks for its parameter size
✓Permissive Apache 2.0 commercial license
✓Broad day-one support for local and cloud inference frameworks
✓Configurable thinking mode for task-specific accuracy
✓Efficient fp8 quantization reduces hardware requirements
✗Self-hosting requires significant GPU VRAM without quantization
✗No official managed API or enterprise SLA from Google
✗Reasoning mode increases token consumption and latency
✗Video input support varies by deployment environment
✗Requires technical expertise for optimal tuning and deployment

zai-org/GLM-5.1

✓Strong multi-step reasoning and coding performance
✓Commercially permissive MIT license
✓Large 200k context window
✓Open-weight with transparent architecture
✓High benchmark scores (Intelligence Index: 51)
✗Higher token pricing compared to many open models
✗Slower inference speed (~44 t/s)
✗High verbosity increases output costs
✗Text-only input/output requires separate vision models
✗Heavy hardware requirements for self-hosting

Full Breakdown

Category
google/gemma-4-31B-itgoogle/gemma-4-31B-it
zai-org/GLM-5.1zai-org/GLM-5.1

Overall Rating

★4.5 / 5
4.2 / 5

Starting Price

0.00 (Self-hosted)
$1.40 / 1M input tokens

Learning Curve

Moderate. Familiarity with local LLM runners (Ollama, vLLM, LM Studio) and basic prompt engineering for reasoning modes is recommended.
Moderate. Requires familiarity with OpenAI-compatible SDKs, prompt engineering for reasoning modes, and token budget management due to verbosity.

Best Suited For

Developers, researchers, and enterprises building custom AI pipelines, local inference setups, or fine-tuning projects requiring strong reasoning and multilingual capabilities.
Software engineering teams, AI agent developers, and researchers requiring strong multi-step reasoning and open-weight deployment flexibility.

Support Quality

Community-driven support via Hugging Face, GitHub, and Discord. Google provides official documentation and developer guides but no dedicated enterprise SLA for the open-weight release.
Standard developer documentation and community support via GitHub and Hugging Face. No dedicated enterprise SLA is publicly advertised for the open-weight version.

Hidden Costs

GPU/TPU infrastructure, electricity, and potential engineering time for deployment and optimization.
High verbosity can significantly increase output token consumption. Self-hosting requires substantial GPU infrastructure due to the 754B parameter size.

Refund Policy

N/A (Open-source model)
Pay-as-you-go model; no refunds on consumed tokens. Unused credits may expire per provider terms.

Platforms

Linux, macOS, Windows (via WSL/containers), Cloud (GCP, AWS, Azure), On-premise servers
Cloud API, Self-hosted (GPU), Hugging Face, ModelScope

Features

Watermark on Free Plan

✗ No
✗ No

Mobile App

✗ No
✗ No

API Access

✓ Yes
✓ Yes
google/gemma-4-31B-it Review →Try Free →
zai-org/GLM-5.1 Review →Try Free →