DeepSeek R1 Distill Qwen 14B vs Phi-3.5-mini-instruct
DeepSeek R1 Distill Qwen 14B leads the LLM Stats Score 11.0 to -3.8.
DeepSeek · Microsoft · Updated for 2026
Which is better?
DeepSeek R1 Distill Qwen 14B leads the overall LLM Stats Score 11.0 to -3.8, ranking #249 overall.
In the 1 individual benchmarks reported for both models, DeepSeek R1 Distill Qwen 14B wins 1; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Qwen 14B
- overall performance matters — it scores 11.0 and ranks #249 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Jan 2025
Choose Phi-3.5-mini-instruct
- you want predictable pricing at $0.10/M input and $0.10/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
4 reported for DeepSeek R1 Distill Qwen 14B · 31 for Phi-3.5-mini-instruct
DeepSeek R1 Distill Qwen 14B outperforms in 1 benchmarks (GPQA), while Phi-3.5-mini-instruct is better at 0 benchmarks.
DeepSeek R1 Distill Qwen 14B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek R1 Distill Qwen 14B has 11.0B more parameters than Phi-3.5-mini-instruct, making it 289.5% larger.
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).
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 14B was released on 2025-01-20, while Phi-3.5-mini-instruct was released on 2024-08-23.
DeepSeek R1 Distill Qwen 14B is 5 months newer than Phi-3.5-mini-instruct.
Jan 20, 2025
1.6 years ago
5mo newerAug 23, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 14B and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 14B vs Phi-3.5-mini-instruct.