Model Comparison
DeepSeek-V3 vs Phi-3.5-mini-instructWhich is better in 2026?
DeepSeek-V3 significantly outperforms across most benchmarks. Phi-3.5-mini-instruct is 4.8x cheaper per token.
Verdict: DeepSeek-V3 vs Phi-3.5-mini-instruct — which is better?
DeepSeek-V3 (by DeepSeek) and Phi-3.5-mini-instruct (by Microsoft) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V3 outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Phi-3.5-mini-instruct is better at 0 benchmarks. DeepSeek-V3 significantly outperforms across most benchmarks.
On price, Phi-3.5-mini-instruct is roughly 4.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3 if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Dec 2024
Choose Phi-3.5-mini-instruct if…
- cost matters — it's about 4.8x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3 outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Phi-3.5-mini-instruct is better at 0 benchmarks.
DeepSeek-V3 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 ($0.27/1M tokens) is 2.7x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).
For output processing, DeepSeek-V3 ($1.10/1M tokens) is 11.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).
In conclusion, DeepSeek-V3 is more expensive than Phi-3.5-mini-instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 has 667.2B more parameters than Phi-3.5-mini-instruct, making it 17557.9% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3 accepts 131,072 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Phi-3.5-mini-instruct is limited to 128,000 tokens.
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Phi-3.5-mini-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 was released on 2024-12-25, while Phi-3.5-mini-instruct was released on 2024-08-23.
DeepSeek-V3 is 4 months newer than Phi-3.5-mini-instruct.
Dec 25, 2024
1.5 years ago
4mo newerAug 23, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3 is available from DeepSeek. Phi-3.5-mini-instruct is available from Azure.
DeepSeek-V3
Phi-3.5-mini-instruct
Outputs Comparison
Key Takeaways
DeepSeek-V3
View detailsDeepSeek
Phi-3.5-mini-instruct
View detailsMicrosoft
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3 and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V3 vs Phi-3.5-mini-instruct.