Model Comparison

DeepSeek R1 Distill Qwen 7B vs Phi-3.5-mini-instruct

DeepSeek R1 Distill Qwen 7B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Distill Qwen 7B outperforms in 1 benchmarks (GPQA), while Phi-3.5-mini-instruct is better at 0 benchmarks.

DeepSeek R1 Distill Qwen 7B significantly outperforms across most benchmarks.

Mon May 04 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

3.8B diff

DeepSeek R1 Distill Qwen 7B has 3.8B more parameters than Phi-3.5-mini-instruct, making it 100.5% larger.

DeepSeek
DeepSeek R1 Distill Qwen 7B
7.6Bparameters
Microsoft
Phi-3.5-mini-instruct
3.8Bparameters
7.6B
DeepSeek R1 Distill Qwen 7B
3.8B
Phi-3.5-mini-instruct

Context Window

Maximum input and output token capacity

Only Phi-3.5-mini-instruct specifies input context (128,000 tokens). Only Phi-3.5-mini-instruct specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 7B
Input- tokens
Output- tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Mon May 04 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 7B

MIT

Open weights

Phi-3.5-mini-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 7B was released on 2025-01-20, while Phi-3.5-mini-instruct was released on 2024-08-23.

DeepSeek R1 Distill Qwen 7B is 5 months newer than Phi-3.5-mini-instruct.

DeepSeek R1 Distill Qwen 7B

Jan 20, 2025

1.3 years ago

5mo newer
Phi-3.5-mini-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

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Key Takeaways

DeepSeek
Higher GPQA score (49.1% vs 30.4%)
Microsoft
Larger context window (128,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 7B
Microsoft
Phi-3.5-mini-instruct

FAQ

Common questions about DeepSeek R1 Distill Qwen 7B vs Phi-3.5-mini-instruct.

Which is better, DeepSeek R1 Distill Qwen 7B or Phi-3.5-mini-instruct?

DeepSeek R1 Distill Qwen 7B significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 7B is made by DeepSeek and Phi-3.5-mini-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Distill Qwen 7B compare to Phi-3.5-mini-instruct in benchmarks?

DeepSeek R1 Distill Qwen 7B scores MATH-500: 92.8%, AIME 2024: 83.3%, GPQA: 49.1%, LiveCodeBench: 37.6%. Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.

What are the context window sizes for DeepSeek R1 Distill Qwen 7B and Phi-3.5-mini-instruct?

DeepSeek R1 Distill Qwen 7B supports an unknown number of tokens and Phi-3.5-mini-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Who makes DeepSeek R1 Distill Qwen 7B and Phi-3.5-mini-instruct?

DeepSeek R1 Distill Qwen 7B is developed by DeepSeek and Phi-3.5-mini-instruct is developed by Microsoft.