Llama 4 Maverick vs Llama 4 Scout
Llama 4 Maverick leads the LLM Stats Score 14.7 to 7.8. Llama 4 Scout is 2.1x cheaper per token.
Meta · Meta · Updated for 2026
Which is better?
Llama 4 Maverick leads the overall LLM Stats Score 14.7 to 7.8, ranking #233 overall.
In the 12 individual benchmarks reported for both models, Llama 4 Maverick wins 11; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 4 Scout is roughly 2.1x 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 Maverick
- overall performance matters — it scores 14.7 and ranks #233 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 11 of 12 exact shared results
Choose Llama 4 Scout
- cost matters — it's about 2.1x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Llama 4 Maverick · 12 for Llama 4 Scout
Llama 4 Maverick outperforms in 11 benchmarks (ChartQA, GPQA, LiveCodeBench, MATH, MathVista, MBPP, MGSM, MMLU, MMLU-Pro, MMMU, TydiQA), while Llama 4 Scout is better at 0 benchmarks.
Llama 4 Maverick significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 4 Maverick ($0.17/1M tokens) is 2.1x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, Llama 4 Maverick ($0.60/1M tokens) is 2.0x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, Llama 4 Maverick is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 4 Maverick has 291.0B more parameters than Llama 4 Scout, making it 267.0% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Llama 4 Maverick's 1,000,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Llama 4 Maverick is limited to 1,000,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Llama 4 Maverick and Llama 4 Scout support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Llama 4 Maverick
Llama 4 Scout
License
Usage and distribution terms
Both models are licensed under Llama 4 Community License Agreement.
Both models share the same licensing terms, providing consistent usage rights.
Llama 4 Community License Agreement
Open weights
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
Both models were released on 2025-04-05.
They likely represent similar generations of model development.
Apr 5, 2025
1.4 years ago
Apr 5, 2025
1.4 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 Maverick is available from DeepInfra, Novita, Lambda, Groq, Fireworks, Together, Sambanova. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
Llama 4 Maverick
Llama 4 Scout
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 4 Maverick and Llama 4 Scout side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 4 Maverick vs Llama 4 Scout.