GLM-5.3 vs Phi-4-multimodal-instruct
Comparing GLM-5.3 and Phi-4-multimodal-instruct across benchmarks, pricing, and capabilities.
Zhipu AI · Microsoft · Updated for 2026
Which is better?
GLM-5.3 and Phi-4-multimodal-instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Phi-4-multimodal-instruct is roughly 34.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose GLM-5.3
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Phi-4-multimodal-instruct
- cost matters — it's about 34.4x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3 and Phi-4-multimodal-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3 ($1.40/1M tokens) is 28.0x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, GLM-5.3 ($4.40/1M tokens) is 44.0x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, GLM-5.3 is more expensive than Phi-4-multimodal-instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3 has 747.4B more parameters than Phi-4-multimodal-instruct, making it 13346.4% larger.
Context Window
Maximum input and output token capacity
GLM-5.3 accepts 1,000,000 input tokens compared to Phi-4-multimodal-instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Phi-4-multimodal-instruct supports multimodal inputs, whereas GLM-5.3 does not.
Phi-4-multimodal-instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3
Phi-4-multimodal-instruct
Release Timeline
When each model was launched
GLM-5.3 was released on 2026-08-14, while Phi-4-multimodal-instruct was released on 2025-02-01.
GLM-5.3 is 19 months newer than Phi-4-multimodal-instruct.
Aug 14, 2026
1 weeks ago
1.5yr newerFeb 1, 2025
1.6 years ago
Knowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while GLM-5.3's cutoff date is not specified.
We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without GLM-5.3's cutoff date.
—
Jun 2024
Provider Availability
GLM-5.3 is available from ZAI. Phi-4-multimodal-instruct is available from DeepInfra.
GLM-5.3
Phi-4-multimodal-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3 and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3 vs Phi-4-multimodal-instruct.