Model Comparison
Llama 3.1 405B Instruct vs Llama 4 ScoutWhich is better in 2026?
Both models are evenly matched across the benchmarks. Llama 4 Scout is 6.6x cheaper per token.
Verdict: Llama 3.1 405B Instruct vs Llama 4 Scout — which is better?
Llama 3.1 405B Instruct (by Meta) and Llama 4 Scout (by Meta) 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 3.1 405B Instruct outperforms in 2 benchmarks (MATH, MMLU), while Llama 4 Scout is better at 2 benchmarks (GPQA, MMLU-Pro). Both models are evenly matched across the benchmarks.
On price, Llama 4 Scout is roughly 6.6x 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 3.1 405B Instruct if…
- you want predictable pricing at $0.89/M input and $0.89/M output
Choose Llama 4 Scout if…
- cost matters — it's about 6.6x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
- you want the most recent training data — it shipped Apr 2025
Performance Benchmarks
Comparative analysis across standard metrics
Llama 3.1 405B Instruct outperforms in 2 benchmarks (MATH, MMLU), while Llama 4 Scout is better at 2 benchmarks (GPQA, MMLU-Pro).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 3.1 405B Instruct ($0.89/1M tokens) is 11.1x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, Llama 3.1 405B Instruct ($0.89/1M tokens) is 3.0x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, Llama 3.1 405B Instruct is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 3.1 405B Instruct has 296.0B more parameters than Llama 4 Scout, making it 271.6% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Llama 3.1 405B Instruct's 128,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Llama 3.1 405B Instruct is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Llama 4 Scout supports multimodal inputs, whereas Llama 3.1 405B Instruct does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
Llama 3.1 405B Instruct
Llama 4 Scout
License
Usage and distribution terms
Llama 3.1 405B Instruct is licensed under Llama 3.1 Community License, while Llama 4 Scout uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.1 Community License
Open weights
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
Llama 3.1 405B Instruct was released on 2024-07-23, while Llama 4 Scout was released on 2025-04-05.
Llama 4 Scout is 9 months newer than Llama 3.1 405B Instruct.
Jul 23, 2024
2.0 years ago
Apr 5, 2025
1.3 years ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
Llama 3.1 405B Instruct
Llama 4 Scout
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Llama 3.1 405B Instruct and Llama 4 Scout side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Llama 3.1 405B Instruct vs Llama 4 Scout.