Model Comparison

DeepSeek R1 Distill Qwen 1.5B vs Phi-3.5-MoE-instruct

Phi-3.5-MoE-instruct significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Phi-3.5-MoE-instruct is better at 1 benchmark (GPQA).

Phi-3.5-MoE-instruct significantly outperforms across most benchmarks.

Tue Apr 07 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
Tue Apr 07 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Microsoft
Phi-3.5-MoE-instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

58.2B diff

Phi-3.5-MoE-instruct has 58.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 3270.8% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
60.0B
Phi-3.5-MoE-instruct

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 1.5B

MIT

Open weights

Phi-3.5-MoE-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Phi-3.5-MoE-instruct was released on 2024-08-23.

DeepSeek R1 Distill Qwen 1.5B is 5 months newer than Phi-3.5-MoE-instruct.

DeepSeek R1 Distill Qwen 1.5B

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
Microsoft
Higher GPQA score (36.8% vs 33.8%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Microsoft
Phi-3.5-MoE-instruct

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs Phi-3.5-MoE-instruct

Phi-3.5-MoE-instruct significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 1.5B 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 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. 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 1.5B is developed by DeepSeek and Phi-3.5-MoE-instruct is developed by Microsoft.