Model Comparison

DeepSeek-R1-0528 vs Phi-3.5-vision-instruct

Comparing DeepSeek-R1-0528 and Phi-3.5-vision-instruct across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1-0528 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
Fri May 01 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
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

666.8B diff

DeepSeek-R1-0528 has 666.8B more parameters than Phi-3.5-vision-instruct, making it 15876.2% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Microsoft
Phi-3.5-vision-instruct
4.2Bparameters
671.0B
DeepSeek-R1-0528
4.2B
Phi-3.5-vision-instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Microsoft
Phi-3.5-vision-instruct
Input- tokens
Output- tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Phi-3.5-vision-instruct supports multimodal inputs, whereas DeepSeek-R1-0528 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-R1-0528

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-R1-0528

MIT

Open weights

Phi-3.5-vision-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Phi-3.5-vision-instruct was released on 2024-08-23.

DeepSeek-R1-0528 is 9 months newer than Phi-3.5-vision-instruct.

DeepSeek-R1-0528

May 28, 2025

11 months ago

9mo 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 (131,072 tokens)
Microsoft
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Microsoft
Phi-3.5-vision-instruct

FAQ

Common questions about DeepSeek-R1-0528 vs Phi-3.5-vision-instruct

DeepSeek-R1-0528 (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-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Phi-3.5-vision-instruct scores ScienceQA: 91.3%, POPE: 86.1%, MMBench: 81.9%, ChartQA: 81.8%, AI2D: 78.1%.
DeepSeek-R1-0528 supports 131K 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-R1-0528 is developed by DeepSeek and Phi-3.5-vision-instruct is developed by Microsoft.