Muse Spark 1.3 vs Phi-4-multimodal-instruct
Muse Spark 1.3 leads the LLM Stats Score 55.4 to 3.1. Phi-4-multimodal-instruct is 2.0x cheaper per token.
Meta · Microsoft · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 55.4 to 3.1, ranking #5 overall.
On price, Phi-4-multimodal-instruct is roughly 2.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark 1.3 also accepts a larger context window (1,048,576 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 Muse Spark 1.3
- overall performance matters — it scores 55.4 and ranks #5 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Phi-4-multimodal-instruct
- cost matters — it's about 2.0x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
11 reported for Muse Spark 1.3 · 15 for Phi-4-multimodal-instruct
Muse Spark 1.3 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, Muse Spark 1.3 ($0.10/1M tokens) is 2.0x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, Muse Spark 1.3 ($0.20/1M tokens) is 2.0x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, Muse Spark 1.3 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
Muse Spark 1.3 accepts 1,048,576 input tokens compared to Phi-4-multimodal-instruct's 128,000 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while Phi-4-multimodal-instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Muse Spark 1.3 and Phi-4-multimodal-instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Muse Spark 1.3
Phi-4-multimodal-instruct
License
Usage and distribution terms
Muse Spark 1.3 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
Muse Spark 1.3 was released on 2026-09-02, while Phi-4-multimodal-instruct was released on 2025-02-01.
Muse Spark 1.3 is 19 months newer than Phi-4-multimodal-instruct.
Sep 2, 2026
0 days ago
1.6yr newerFeb 1, 2025
1.6 years ago
Knowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while Muse Spark 1.3'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 Muse Spark 1.3's cutoff date.
—
Jun 2024
Provider Availability
Muse Spark 1.3 is available from Meta Model API. Phi-4-multimodal-instruct is available from DeepInfra.
Muse Spark 1.3
Phi-4-multimodal-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Muse Spark 1.3 and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Muse Spark 1.3 vs Phi-4-multimodal-instruct.