Model Comparison

GLM-5 vs Phi-3.5-vision-instructWhich is better in 2026?

Comparing GLM-5 and Phi-3.5-vision-instruct across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Phi-3.5-vision-instruct — which is better?

GLM-5 (by Zhipu AI) and Phi-3.5-vision-instruct (by Microsoft) 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.

Choose GLM-5 if…

  • you want the most recent training data — it shipped Feb 2026

Choose Phi-3.5-vision-instruct if…

  • you are already invested in the Microsoft ecosystem
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Phi-3.5-vision-instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

739.8B diff

GLM-5 has 739.8B more parameters than Phi-3.5-vision-instruct, making it 17614.3% larger.

Zhipu AI
GLM-5
744.0Bparameters
Microsoft
Phi-3.5-vision-instruct
4.2Bparameters
744.0B
GLM-5
4.2B
Phi-3.5-vision-instruct

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
Microsoft
Phi-3.5-vision-instruct
Input- tokens
Output- tokens
Sat Jun 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Phi-3.5-vision-instruct supports multimodal inputs, whereas GLM-5 does not.

Phi-3.5-vision-instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Phi-3.5-vision-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

GLM-5

MIT

Open weights

Phi-3.5-vision-instruct

MIT

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Phi-3.5-vision-instruct was released on 2024-08-23.

GLM-5 is 18 months newer than Phi-3.5-vision-instruct.

GLM-5

Feb 11, 2026

3 months ago

1.5yr newer
Phi-3.5-vision-instruct

Aug 23, 2024

1.8 years 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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

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

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Microsoft
Phi-3.5-vision-instruct

FAQ

Common questions about GLM-5 vs Phi-3.5-vision-instruct.

Which is better, GLM-5 or Phi-3.5-vision-instruct?

GLM-5 (Zhipu AI) and Phi-3.5-vision-instruct (Microsoft) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GLM-5 compare to Phi-3.5-vision-instruct in benchmarks?

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%. Phi-3.5-vision-instruct scores ScienceQA: 91.3%, POPE: 86.1%, MMBench: 81.9%, ChartQA: 81.8%, AI2D: 78.1%.

What are the context window sizes for GLM-5 and Phi-3.5-vision-instruct?

GLM-5 supports 200K tokens and Phi-3.5-vision-instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5 and Phi-3.5-vision-instruct?

Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Phi-3.5-vision-instruct?

GLM-5 is developed by Zhipu AI and Phi-3.5-vision-instruct is developed by Microsoft.

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