Model Comparison

GLM-5 vs Step3-VL-10B

Comparing GLM-5 and Step3-VL-10B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Step3-VL-10B don'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

Cost data unavailable.

Lowest available price from all providers
Tue Apr 07 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
StepFun
Step3-VL-10B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

734.0B diff

GLM-5 has 734.0B more parameters than Step3-VL-10B, making it 7340.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
StepFun
Step3-VL-10B
10.0Bparameters
744.0B
GLM-5
10.0B
Step3-VL-10B

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
StepFun
Step3-VL-10B
Input- tokens
Output- tokens
Tue Apr 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Step3-VL-10B supports multimodal inputs, whereas GLM-5 does not.

Step3-VL-10B can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Step3-VL-10B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Step3-VL-10B uses Apache 2.0.

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

GLM-5

MIT

Open weights

Step3-VL-10B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Step3-VL-10B was released on 2026-01-15.

GLM-5 is 1 month newer than Step3-VL-10B.

GLM-5

Feb 11, 2026

1 months ago

3w newer
Step3-VL-10B

Jan 15, 2026

2 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
StepFun
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
StepFun
Step3-VL-10B

FAQ

Common questions about GLM-5 vs Step3-VL-10B

GLM-5 (Zhipu AI) and Step3-VL-10B (StepFun) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Step3-VL-10B scores MMBench: 91.8%, AIME 2025: 87.7%, MathVista: 84.0%, MMMU: 78.1%, MathVision: 70.8%.
GLM-5 supports 200K tokens and Step3-VL-10B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
GLM-5 is developed by Zhipu AI and Step3-VL-10B is developed by StepFun.