GPT-4o vs Llama 4 Scout
GPT-4o leads the LLM Stats Score 14.1 to 7.8. Llama 4 Scout is 32.4x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-4o leads the overall LLM Stats Score 14.1 to 7.8, ranking #254 overall.
In the 7 individual benchmarks reported for both models, GPT-4o wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 4 Scout is roughly 32.4x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4o
- overall performance matters — it scores 14.1 and ranks #254 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 7 exact shared results
Choose Llama 4 Scout
- cost matters — it's about 32.4x 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
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
38 reported for GPT-4o · 12 for Llama 4 Scout
GPT-4o outperforms in 4 benchmarks (GPQA, MMLU, MMLU-Pro, MMMU), while Llama 4 Scout is better at 3 benchmarks (ChartQA, DocVQA, MathVista).
GPT-4o 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, GPT-4o ($2.50/1M tokens) is 31.3x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, GPT-4o ($10.00/1M tokens) is 33.3x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, GPT-4o 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 GPT-4o's 128,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while GPT-4o is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-4o and Llama 4 Scout support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4o
Llama 4 Scout
License
Usage and distribution terms
GPT-4o is licensed under a proprietary 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.
Proprietary
Closed source
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
GPT-4o was released on 2024-08-06, while Llama 4 Scout was released on 2025-04-05.
Llama 4 Scout is 8 months newer than GPT-4o.
Aug 6, 2024
2.2 years ago
Apr 5, 2025
1.5 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
GPT-4o is available from Azure, OpenAI. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
GPT-4o
Llama 4 Scout
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4o and Llama 4 Scout side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4o vs Llama 4 Scout.