Model Comparison

DeepSeek-R1 vs Phi-3.5-mini-instruct

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

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Phi-3.5-mini-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

Phi-3.5-mini-instruct costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 5.5x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 21.9x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

In conclusion, DeepSeek-R1 is more expensive than Phi-3.5-mini-instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat May 02 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

667.2B diff

DeepSeek-R1 has 667.2B more parameters than Phi-3.5-mini-instruct, making it 17557.9% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
Microsoft
Phi-3.5-mini-instruct
3.8Bparameters
671.0B
DeepSeek-R1
3.8B
Phi-3.5-mini-instruct

Context Window

Maximum input and output token capacity

DeepSeek-R1 accepts 131,072 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Phi-3.5-mini-instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Sat May 02 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

MIT

Open weights

Phi-3.5-mini-instruct

MIT

Open weights

Release Timeline

When each model was launched

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

DeepSeek-R1 is 5 months newer than Phi-3.5-mini-instruct.

DeepSeek-R1

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

Provider Availability

DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Phi-3.5-mini-instruct is available from Azure.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

Phi-3.5-mini-instruct

azure logo
Azure
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Microsoft
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

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

FAQ

Common questions about DeepSeek-R1 vs Phi-3.5-mini-instruct.

Which is better, DeepSeek-R1 or Phi-3.5-mini-instruct?

DeepSeek-R1 (DeepSeek) and Phi-3.5-mini-instruct (Microsoft) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-R1 compare to Phi-3.5-mini-instruct in benchmarks?

Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.

Is DeepSeek-R1 cheaper than Phi-3.5-mini-instruct?

Phi-3.5-mini-instruct is 5.5x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure.

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

DeepSeek-R1 supports 131K 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.

What are the main differences between DeepSeek-R1 and Phi-3.5-mini-instruct?

Key differences include context window (131K vs 128K), input pricing ($0.55 vs $0.10/M). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1 and Phi-3.5-mini-instruct?

DeepSeek-R1 is developed by DeepSeek and Phi-3.5-mini-instruct is developed by Microsoft.