Model Comparison

DeepSeek VL2 Tiny vs Phi-3.5-MoE-instruct

Comparing DeepSeek VL2 Tiny and Phi-3.5-MoE-instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 Tiny and Phi-3.5-MoE-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

57.0B diff

Phi-3.5-MoE-instruct has 57.0B more parameters than DeepSeek VL2 Tiny, making it 1900.0% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
3.0B
DeepSeek VL2 Tiny
60.0B
Phi-3.5-MoE-instruct

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Tiny supports multimodal inputs, whereas Phi-3.5-MoE-instruct does not.

DeepSeek VL2 Tiny can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2 Tiny

Text
Images
Audio
Video

Phi-3.5-MoE-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while Phi-3.5-MoE-instruct uses MIT.

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

DeepSeek VL2 Tiny

deepseek

Open weights

Phi-3.5-MoE-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while Phi-3.5-MoE-instruct was released on 2024-08-23.

DeepSeek VL2 Tiny is 4 months newer than Phi-3.5-MoE-instruct.

DeepSeek VL2 Tiny

Dec 13, 2024

1.5 years ago

3mo newer
Phi-3.5-MoE-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

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Key Takeaways

DeepSeek
Supports multimodal inputs
Microsoft

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
Microsoft
Phi-3.5-MoE-instruct

FAQ

Common questions about DeepSeek VL2 Tiny vs Phi-3.5-MoE-instruct.

Which is better, DeepSeek VL2 Tiny or Phi-3.5-MoE-instruct?

DeepSeek VL2 Tiny (DeepSeek) and Phi-3.5-MoE-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 DeepSeek VL2 Tiny compare to Phi-3.5-MoE-instruct in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. Phi-3.5-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%.

What are the main differences between DeepSeek VL2 Tiny and Phi-3.5-MoE-instruct?

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

Who makes DeepSeek VL2 Tiny and Phi-3.5-MoE-instruct?

DeepSeek VL2 Tiny is developed by DeepSeek and Phi-3.5-MoE-instruct is developed by Microsoft.