Phi-3.5-mini-instruct vs Phi 4
Phi 4 leads the LLM Stats Score 5.4 to -3.8. Phi 4 is 1.1x cheaper per token.
Microsoft · Microsoft · Updated for 2026
Which is better?
Phi 4 leads the overall LLM Stats Score 5.4 to -3.8, ranking #296 overall.
In the 7 individual benchmarks reported for both models, Phi 4 wins 7; this is a narrower head-to-head signal than the composite indexes.
On price, Phi 4 is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Phi-3.5-mini-instruct also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Phi-3.5-mini-instruct
- you process long inputs — it offers a 128,000 token context window
Choose Phi 4
- overall performance matters — it scores 5.4 and ranks #296 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 7 of 7 exact shared results
- cost matters — it's about 1.1x cheaper per token
- you want the most recent training data — it shipped Dec 2024
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
31 reported for Phi-3.5-mini-instruct · 13 for Phi 4
Phi-3.5-mini-instruct outperforms in 0 benchmarks, while Phi 4 is better at 7 benchmarks (Arena Hard, GPQA, HumanEval, MATH, MGSM, MMLU, MMLU-Pro).
Phi 4 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Phi-3.5-mini-instruct ($0.10/1M tokens) is 1.4x more expensive than Phi 4 ($0.07/1M tokens).
For output processing, Phi-3.5-mini-instruct ($0.10/1M tokens) is 1.4x cheaper than Phi 4 ($0.14/1M tokens).
In conclusion, Phi-3.5-mini-instruct is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Phi 4 has 10.9B more parameters than Phi-3.5-mini-instruct, making it 286.8% larger.
Context Window
Maximum input and output token capacity
Phi-3.5-mini-instruct accepts 128,000 input tokens compared to Phi 4's 16,384 tokens. Phi-3.5-mini-instruct can generate longer responses up to 128,000 tokens, while Phi 4 is limited to 16,384 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
Phi-3.5-mini-instruct was released on 2024-08-23, while Phi 4 was released on 2024-12-12.
Phi 4 is 4 months newer than Phi-3.5-mini-instruct.
Aug 23, 2024
2.1 years ago
Dec 12, 2024
1.8 years ago
3mo newerKnowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Phi-3.5-mini-instruct's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Phi-3.5-mini-instruct's cutoff date.
—
Jun 2024
Provider Availability
Phi-3.5-mini-instruct is available from Azure. Phi 4 is available from DeepInfra.
Phi-3.5-mini-instruct
Phi 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Phi-3.5-mini-instruct and Phi 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi-3.5-mini-instruct vs Phi 4.