Model Comparison

Llama 4 Scout vs Phi-3.5-mini-instructWhich is better in 2026?

Llama 4 Scout significantly outperforms across most benchmarks. Phi-3.5-mini-instruct is 1.4x cheaper per token.

Verdict: Llama 4 Scout vs Phi-3.5-mini-instruct — which is better?

Llama 4 Scout (by Meta) and Phi-3.5-mini-instruct (by Microsoft) 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.

Llama 4 Scout outperforms in 5 benchmarks (GPQA, MATH, MGSM, MMLU, MMLU-Pro), while Phi-3.5-mini-instruct is better at 1 benchmark (MBPP). Llama 4 Scout significantly outperforms across most benchmarks.

On price, Phi-3.5-mini-instruct is roughly 1.4x 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.

Choose Llama 4 Scout if…

  • you want the strongest raw capability — it leads on 5 of 6 shared benchmarks
  • 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-3.5-mini-instruct if…

  • cost matters — it's about 1.4x cheaper per token

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Llama 4 Scout outperforms in 5 benchmarks (GPQA, MATH, MGSM, MMLU, MMLU-Pro), while Phi-3.5-mini-instruct is better at 1 benchmark (MBPP).

Llama 4 Scout significantly outperforms across most benchmarks.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Phi-3.5-mini-instruct costs less

For input processing, Llama 4 Scout ($0.08/1M tokens) is 1.3x cheaper than Phi-3.5-mini-instruct ($0.10/1M tokens).

For output processing, Llama 4 Scout ($0.30/1M tokens) is 3.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

In conclusion, Llama 4 Scout is more expensive than Phi-3.5-mini-instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Jul 21 2026 • llm-stats.com
Meta
Llama 4 Scout
Input tokens$0.08
Output tokens$0.30
Best providerDeepinfra
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

105.2B diff

Llama 4 Scout has 105.2B more parameters than Phi-3.5-mini-instruct, making it 2768.4% larger.

Meta
Llama 4 Scout
109.0Bparameters
Microsoft
Phi-3.5-mini-instruct
3.8Bparameters
109.0B
Llama 4 Scout
3.8B
Phi-3.5-mini-instruct

Context Window

Maximum input and output token capacity

Llama 4 Scout accepts 10,000,000 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Phi-3.5-mini-instruct is limited to 128,000 tokens.

Meta
Llama 4 Scout
Input10,000,000 tokens
Output10,000,000 tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 4 Scout supports multimodal inputs, whereas Phi-3.5-mini-instruct 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

Text
Images
Audio
Video

Phi-3.5-mini-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 4 Scout is licensed under Llama 4 Community License Agreement, while Phi-3.5-mini-instruct uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Llama 4 Scout

Llama 4 Community License Agreement

Open weights

Phi-3.5-mini-instruct

MIT

Open weights

Release Timeline

When each model was launched

Llama 4 Scout was released on 2025-04-05, while Phi-3.5-mini-instruct was released on 2024-08-23.

Llama 4 Scout is 8 months newer than Phi-3.5-mini-instruct.

Llama 4 Scout

Apr 5, 2025

1.3 years ago

7mo newer
Phi-3.5-mini-instruct

Aug 23, 2024

1.9 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. Phi-3.5-mini-instruct is available from Azure.

Llama 4 Scout

deepinfra logo
Deepinfra
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
lambda logo
Lambda
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
novita logo
Novita
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
groq logo
Groq
Input Price:Input: $0.11/1MOutput Price:Output: $0.34/1M
fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
together logo
Together
Input Price:Input: $0.18/1MOutput Price:Output: $0.59/1M

Phi-3.5-mini-instruct

azure logo
Azure
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Meta
Larger context window (10,000,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Higher GPQA score (57.2% vs 30.4%)
Higher MATH score (50.3% vs 48.5%)
Higher MGSM score (90.6% vs 47.9%)
Higher MMLU score (79.6% vs 69.0%)
Higher MMLU-Pro score (74.3% vs 47.4%)
Microsoft
Less expensive output tokens
Higher MBPP score (69.6% vs 67.8%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Llama 4 Scout and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.

Llama 4 Scout
✓ Preferred
Phi-3.5-mini-instruct
Open in Playground
AI Model Comparison Table
Feature
Meta
Llama 4 Scout
Microsoft
Phi-3.5-mini-instruct

FAQ

Common questions about Llama 4 Scout vs Phi-3.5-mini-instruct.

Which is better, Llama 4 Scout or Phi-3.5-mini-instruct?

Llama 4 Scout significantly outperforms across most benchmarks. Llama 4 Scout is made by Meta and Phi-3.5-mini-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Llama 4 Scout compare to Phi-3.5-mini-instruct in benchmarks?

Llama 4 Scout scores DocVQA: 94.4%, MGSM: 90.6%, ChartQA: 88.8%, MMLU: 79.6%, MMLU-Pro: 74.3%. Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.

Is Llama 4 Scout cheaper than Phi-3.5-mini-instruct?

Llama 4 Scout is 1.3x cheaper for input tokens. Llama 4 Scout costs $0.08/M input and $0.30/M output via deepinfra. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure.

What are the context window sizes for Llama 4 Scout and Phi-3.5-mini-instruct?

Llama 4 Scout supports 10.0M tokens and Phi-3.5-mini-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 4 Scout and Phi-3.5-mini-instruct?

Key differences include context window (10.0M vs 128K), input pricing ($0.08 vs $0.10/M), multimodal support (yes vs no), licensing (Llama 4 Community License Agreement vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 4 Scout and Phi-3.5-mini-instruct?

Llama 4 Scout is developed by Meta and Phi-3.5-mini-instruct is developed by Microsoft.

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