Model Comparison

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

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2-Exp outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Phi-3.5-MoE-instruct is better at 0 benchmarks.

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Microsoft
Phi-3.5-MoE-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

625.0B diff

DeepSeek-V3.2-Exp has 625.0B more parameters than Phi-3.5-MoE-instruct, making it 1041.7% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
685.0B
DeepSeek-V3.2-Exp
60.0B
Phi-3.5-MoE-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-MoE-instruct
Input- tokens
Output- tokens
Thu Apr 16 2026 • llm-stats.com

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-MoE-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-MoE-instruct was released on 2024-08-23.

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

DeepSeek-V3.2-Exp

Sep 29, 2025

6 months ago

1.1yr newer
Phi-3.5-MoE-instruct

Aug 23, 2024

1.6 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
Larger context window (163,840 tokens)
Higher GPQA score (79.9% vs 36.8%)
Higher MMLU-Pro score (85.0% vs 45.3%)
Microsoft

Detailed Comparison

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

FAQ

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

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and Phi-3.5-MoE-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
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-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%.
DeepSeek-V3.2-Exp supports 164K tokens and Phi-3.5-MoE-instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
DeepSeek-V3.2-Exp is developed by DeepSeek and Phi-3.5-MoE-instruct is developed by Microsoft.