Model Comparison

DeepSeek R1 Distill Qwen 32B vs Phi-3.5-MoE-instruct

DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Distill Qwen 32B outperforms in 1 benchmarks (GPQA), while Phi-3.5-MoE-instruct is better at 0 benchmarks.

DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.

Fri Apr 17 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
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 32B
Input tokens$0.12
Output tokens$0.18
Best providerDeepinfra
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

27.2B diff

Phi-3.5-MoE-instruct has 27.2B more parameters than DeepSeek R1 Distill Qwen 32B, making it 82.9% larger.

DeepSeek
DeepSeek R1 Distill Qwen 32B
32.8Bparameters
Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
32.8B
DeepSeek R1 Distill Qwen 32B
60.0B
Phi-3.5-MoE-instruct

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Qwen 32B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Qwen 32B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 32B
Input128,000 tokens
Output128,000 tokens
Microsoft
Phi-3.5-MoE-instruct
Input- tokens
Output- tokens
Fri Apr 17 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 R1 Distill Qwen 32B

MIT

Open weights

Phi-3.5-MoE-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 32B was released on 2025-01-20, while Phi-3.5-MoE-instruct was released on 2024-08-23.

DeepSeek R1 Distill Qwen 32B is 5 months newer than Phi-3.5-MoE-instruct.

DeepSeek R1 Distill Qwen 32B

Jan 20, 2025

1.2 years ago

5mo 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 (128,000 tokens)
Higher GPQA score (62.1% vs 36.8%)
Microsoft

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 32B
Microsoft
Phi-3.5-MoE-instruct

FAQ

Common questions about DeepSeek R1 Distill Qwen 32B vs Phi-3.5-MoE-instruct

DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 32B 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 R1 Distill Qwen 32B scores MATH-500: 94.3%, AIME 2024: 83.3%, GPQA: 62.1%, LiveCodeBench: 57.2%. Phi-3.5-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%.
DeepSeek R1 Distill Qwen 32B supports 128K 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 R1 Distill Qwen 32B is developed by DeepSeek and Phi-3.5-MoE-instruct is developed by Microsoft.