Model Comparison
Llama 4 Scout vs o1-miniWhich is better in 2026?
o1-mini significantly outperforms across most benchmarks. Llama 4 Scout is 38.9x cheaper per token.
Verdict: Llama 4 Scout vs o1-mini — which is better?
Llama 4 Scout (by Meta) and o1-mini (by OpenAI) 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 0 benchmarks, while o1-mini is better at 2 benchmarks (GPQA, MMLU). o1-mini significantly outperforms across most benchmarks.
On price, Llama 4 Scout is roughly 38.9x 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…
- cost matters — it's about 38.9x 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
- you need open weights you can self-host or fine-tune
Choose o1-mini if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
Performance Benchmarks
Comparative analysis across standard metrics
Llama 4 Scout outperforms in 0 benchmarks, while o1-mini is better at 2 benchmarks (GPQA, MMLU).
o1-mini significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 4 Scout ($0.08/1M tokens) is 37.5x cheaper than o1-mini ($3.00/1M tokens).
For output processing, Llama 4 Scout ($0.30/1M tokens) is 40.0x cheaper than o1-mini ($12.00/1M tokens).
In conclusion, o1-mini is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to o1-mini's 128,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while o1-mini is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Llama 4 Scout supports multimodal inputs, whereas o1-mini 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
o1-mini
License
Usage and distribution terms
Llama 4 Scout is licensed under Llama 4 Community License Agreement, while o1-mini uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 4 Community License Agreement
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Llama 4 Scout was released on 2025-04-05, while o1-mini was released on 2024-09-12.
Llama 4 Scout is 7 months newer than o1-mini.
Apr 5, 2025
1.2 years ago
6mo newerSep 12, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. o1-mini is available from OpenAI, Azure.
Llama 4 Scout
o1-mini
Outputs Comparison
Key Takeaways
o1-mini
View detailsOpenAI
Detailed Comparison
| Feature | | |
|---|
FAQ
Common questions about Llama 4 Scout vs o1-mini.