Llama 4 Scout vs Phi 4
Llama 4 Scout and Phi 4 are closely matched at 7.8 and 5.4 on the LLM Stats Score. Phi 4 is 1.5x cheaper per token.
Meta · Microsoft · Updated for 2026
Which is better?
Llama 4 Scout and Phi 4 are closely matched on the overall LLM Stats Score at 7.8 and 5.4.
In the 5 individual benchmarks reported for both models, Llama 4 Scout wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Phi 4 is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 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 Llama 4 Scout
- you value its reported benchmark strengths — it wins 3 of 5 exact shared results
- you process long inputs — it offers a 10,000,000 token context window
- you want the most recent training data — it shipped Apr 2025
Choose Phi 4
- cost matters — it's about 1.5x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for Llama 4 Scout · 13 for Phi 4
Llama 4 Scout outperforms in 3 benchmarks (GPQA, MGSM, MMLU-Pro), while Phi 4 is better at 2 benchmarks (MATH, MMLU).
Llama 4 Scout has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 4 Scout ($0.08/1M tokens) is 1.1x more expensive than Phi 4 ($0.07/1M tokens).
For output processing, Llama 4 Scout ($0.30/1M tokens) is 2.1x more expensive than Phi 4 ($0.14/1M tokens).
In conclusion, Llama 4 Scout is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 4 Scout has 94.3B more parameters than Phi 4, making it 641.5% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Phi 4's 16,384 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Phi 4 is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
Llama 4 Scout supports multimodal inputs, whereas Phi 4 does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
Llama 4 Scout
Phi 4
License
Usage and distribution terms
Llama 4 Scout is licensed under Llama 4 Community License Agreement, while Phi 4 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 4 Community License Agreement
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Llama 4 Scout was released on 2025-04-05, while Phi 4 was released on 2024-12-12.
Llama 4 Scout is 4 months newer than Phi 4.
Apr 5, 2025
1.4 years ago
3mo newerDec 12, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Llama 4 Scout's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Llama 4 Scout's cutoff date.
—
Jun 2024
Provider Availability
Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. Phi 4 is available from DeepInfra.
Llama 4 Scout
Phi 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 4 Scout and Phi 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 4 Scout vs Phi 4.