GPT-6 Rosalind vs Phi-4-multimodal-instruct
Comparing GPT-6 Rosalind and Phi-4-multimodal-instruct across benchmarks, pricing, and capabilities.
OpenAI · Microsoft · Updated for 2026
Which is better?
GPT-6 Rosalind and Phi-4-multimodal-instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Phi-4-multimodal-instruct is roughly 480.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6 Rosalind
- you want the most recent training data — it shipped Oct 2026
Choose Phi-4-multimodal-instruct
- cost matters — it's about 480.0x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
0 reported for GPT-6 Rosalind · 15 for Phi-4-multimodal-instruct
GPT-6 Rosalind and Phi-4-multimodal-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Rosalind ($15.00/1M tokens) is 300.0x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, GPT-6 Rosalind ($75.00/1M tokens) is 750.0x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, GPT-6 Rosalind 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
Only Phi-4-multimodal-instruct specifies input context (128,000 tokens). Only Phi-4-multimodal-instruct specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both GPT-6 Rosalind and Phi-4-multimodal-instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6 Rosalind
Phi-4-multimodal-instruct
License
Usage and distribution terms
GPT-6 Rosalind 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-6 Rosalind was released on 2026-10-30, while Phi-4-multimodal-instruct was released on 2025-02-01.
GPT-6 Rosalind is 21 months newer than Phi-4-multimodal-instruct.
Oct 30, 2026
2 days ago
1.7yr newerFeb 1, 2025
1.7 years ago
Knowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while GPT-6 Rosalind's cutoff date is not specified.
We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without GPT-6 Rosalind's cutoff date.
—
Jun 2024
Provider Availability
GPT-6 Rosalind is available from OpenAI. Phi-4-multimodal-instruct is available from DeepInfra.
GPT-6 Rosalind
Phi-4-multimodal-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Rosalind and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Rosalind vs Phi-4-multimodal-instruct.