Model Comparison
Phi-4-multimodal-instruct vs Pixtral LargeWhich is better in 2026?
Pixtral Large significantly outperforms across most benchmarks. Phi-4-multimodal-instruct is 48.0x cheaper per token.
Verdict: Phi-4-multimodal-instruct vs Pixtral Large — which is better?
Phi-4-multimodal-instruct (by Microsoft) and Pixtral Large (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Phi-4-multimodal-instruct outperforms in 0 benchmarks, while Pixtral Large is better at 5 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMMU). Pixtral Large significantly outperforms across most benchmarks.
On price, Phi-4-multimodal-instruct is roughly 48.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Phi-4-multimodal-instruct if…
- cost matters — it's about 48.0x cheaper per token
- you want the most recent training data — it shipped Feb 2025
Choose Pixtral Large if…
- you want the strongest raw capability — it leads on 5 of 5 shared benchmarks
Performance Benchmarks
Comparative analysis across standard metrics
Phi-4-multimodal-instruct outperforms in 0 benchmarks, while Pixtral Large is better at 5 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMMU).
Pixtral Large significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Phi-4-multimodal-instruct ($0.05/1M tokens) is 40.0x cheaper than Pixtral Large ($2.00/1M tokens).
For output processing, Phi-4-multimodal-instruct ($0.10/1M tokens) is 60.0x cheaper than Pixtral Large ($6.00/1M tokens).
In conclusion, Pixtral Large is more expensive than Phi-4-multimodal-instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Pixtral Large has 118.4B more parameters than Phi-4-multimodal-instruct, making it 2114.3% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Both Phi-4-multimodal-instruct and Pixtral Large support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Phi-4-multimodal-instruct
Pixtral Large
License
Usage and distribution terms
Phi-4-multimodal-instruct is licensed under MIT, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Mistral Research License (MRL) for research; Mistral Commercial License for commercial use
Open weights
Release Timeline
When each model was launched
Phi-4-multimodal-instruct was released on 2025-02-01, while Pixtral Large was released on 2024-11-18.
Phi-4-multimodal-instruct is 3 months newer than Pixtral Large.
Feb 1, 2025
1.5 years ago
2mo newerNov 18, 2024
1.7 years ago
Knowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while Pixtral Large'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 Pixtral Large's cutoff date.
Jun 2024
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Provider Availability
Phi-4-multimodal-instruct is available from DeepInfra. Pixtral Large is available from Mistral AI.
Phi-4-multimodal-instruct
Pixtral Large
Outputs Comparison
Key Takeaways
Pixtral Large
View detailsMistral AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Phi-4-multimodal-instruct and Pixtral Large side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Phi-4-multimodal-instruct vs Pixtral Large.