GPT-4.1 nano vs Phi-4-multimodal-instruct
GPT-4.1 nano and Phi-4-multimodal-instruct are closely matched at 1.9 and 3.0 on the LLM Stats Score. Phi-4-multimodal-instruct is 2.8x cheaper per token.
OpenAI · Microsoft · Updated for 2026
Which is better?
GPT-4.1 nano and Phi-4-multimodal-instruct are closely matched on the overall LLM Stats Score at 1.9 and 3.0.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Phi-4-multimodal-instruct is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-4.1 nano also accepts a larger context window (1,047,576 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-4.1 nano
- you process long inputs — it offers a 1,047,576 token context window
- you want the most recent training data — it shipped Apr 2025
Choose Phi-4-multimodal-instruct
- cost matters — it's about 2.8x cheaper per token
- 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
24 reported for GPT-4.1 nano · 15 for Phi-4-multimodal-instruct
GPT-4.1 nano outperforms in 1 benchmarks (MMMU), while Phi-4-multimodal-instruct is better at 1 benchmark (MathVista).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4.1 nano ($0.10/1M tokens) is 2.0x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, GPT-4.1 nano ($0.40/1M tokens) is 4.0x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, GPT-4.1 nano is more expensive than Phi-4-multimodal-instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4.1 nano accepts 1,047,576 input tokens compared to Phi-4-multimodal-instruct's 128,000 tokens. Phi-4-multimodal-instruct can generate longer responses up to 128,000 tokens, while GPT-4.1 nano is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-4.1 nano and Phi-4-multimodal-instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4.1 nano
Phi-4-multimodal-instruct
License
Usage and distribution terms
GPT-4.1 nano is licensed under a proprietary license, while Phi-4-multimodal-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-4.1 nano was released on 2025-04-14, while Phi-4-multimodal-instruct was released on 2025-02-01.
GPT-4.1 nano is 2 months newer than Phi-4-multimodal-instruct.
Apr 14, 2025
1.4 years ago
2mo newerFeb 1, 2025
1.6 years ago
Knowledge Cutoff
When training data ends
GPT-4.1 nano has a knowledge cutoff of 2024-05-31, while Phi-4-multimodal-instruct has a cutoff of 2024-06-01.
Phi-4-multimodal-instruct has more recent training data (up to 2024-06-01), making it potentially better informed about events through that date compared to GPT-4.1 nano (2024-05-31).
May 2024
Jun 2024
1 mo newerProvider Availability
GPT-4.1 nano is available from OpenAI. Phi-4-multimodal-instruct is available from DeepInfra.
GPT-4.1 nano
Phi-4-multimodal-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4.1 nano and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4.1 nano vs Phi-4-multimodal-instruct.