Model Comparison

DeepSeek-V3.2-Exp vs Phi-3.5-vision-instruct

Comparing DeepSeek-V3.2-Exp and Phi-3.5-vision-instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Exp 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

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Microsoft
Phi-3.5-vision-instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

680.8B diff

DeepSeek-V3.2-Exp has 680.8B more parameters than Phi-3.5-vision-instruct, making it 16209.5% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Microsoft
Phi-3.5-vision-instruct
4.2Bparameters
685.0B
DeepSeek-V3.2-Exp
4.2B
Phi-3.5-vision-instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Microsoft
Phi-3.5-vision-instruct
Input- tokens
Output- tokens
Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Phi-3.5-vision-instruct supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.

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

DeepSeek-V3.2-Exp

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.

DeepSeek-V3.2-Exp

MIT

Open weights

Phi-3.5-vision-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Phi-3.5-vision-instruct was released on 2024-08-23.

DeepSeek-V3.2-Exp is 13 months newer than Phi-3.5-vision-instruct.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

1.1yr newer
Phi-3.5-vision-instruct

Aug 23, 2024

1.7 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

DeepSeek
Larger context window (163,840 tokens)
Microsoft
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Microsoft
Phi-3.5-vision-instruct

FAQ

Common questions about DeepSeek-V3.2-Exp vs Phi-3.5-vision-instruct

DeepSeek-V3.2-Exp (DeepSeek) 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.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Phi-3.5-vision-instruct scores ScienceQA: 91.3%, POPE: 86.1%, MMBench: 81.9%, ChartQA: 81.8%, AI2D: 78.1%.
DeepSeek-V3.2-Exp supports 164K 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.
Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Phi-3.5-vision-instruct is developed by Microsoft.