GPT-3.5 Turbo vs Phi-3.5-mini-instruct
GPT-3.5 Turbo and Phi-3.5-mini-instruct are closely matched at -9.4 and -3.8 on the LLM Stats Score. Phi-3.5-mini-instruct is 7.5x cheaper per token.
OpenAI · Microsoft · Updated for 2026
Which is better?
GPT-3.5 Turbo and Phi-3.5-mini-instruct are closely matched on the overall LLM Stats Score at -9.4 and -3.8.
In the 5 individual benchmarks reported for both models, GPT-3.5 Turbo wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Phi-3.5-mini-instruct is roughly 7.5x 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 GPT-3.5 Turbo
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
Choose Phi-3.5-mini-instruct
- cost matters — it's about 7.5x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Aug 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for GPT-3.5 Turbo · 31 for Phi-3.5-mini-instruct
GPT-3.5 Turbo outperforms in 4 benchmarks (GPQA, HumanEval, MGSM, MMLU), while Phi-3.5-mini-instruct is better at 1 benchmark (MATH).
GPT-3.5 Turbo 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, GPT-3.5 Turbo ($0.50/1M tokens) is 5.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).
For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 15.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).
In conclusion, GPT-3.5 Turbo is more expensive than Phi-3.5-mini-instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Phi-3.5-mini-instruct accepts 128,000 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. Phi-3.5-mini-instruct can generate longer responses up to 128,000 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
License
Usage and distribution terms
GPT-3.5 Turbo is licensed under a proprietary license, while Phi-3.5-mini-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
GPT-3.5 Turbo was released on 2023-03-21, while Phi-3.5-mini-instruct was released on 2024-08-23.
Phi-3.5-mini-instruct is 17 months newer than GPT-3.5 Turbo.
Mar 21, 2023
3.6 years ago
Aug 23, 2024
2.1 years ago
1.4yr newerKnowledge Cutoff
When training data ends
GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while Phi-3.5-mini-instruct's cutoff date is not specified.
We can confirm GPT-3.5 Turbo's training data extends to 2021-09-30, but cannot make a direct comparison without Phi-3.5-mini-instruct's cutoff date.
Sep 2021
—
Provider Availability
GPT-3.5 Turbo is available from Azure, OpenAI. Phi-3.5-mini-instruct is available from Azure.
GPT-3.5 Turbo
Phi-3.5-mini-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-3.5 Turbo and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-3.5 Turbo vs Phi-3.5-mini-instruct.