Llama 4 Maverick wins on coding (58 vs 54) and writing quality. Llama 4 Scout wins on price ($0.5 vs $0.6/1M input) and context window (512K vs 256K). For most workflows, Llama 4 Maverick is the stronger default — best flexible option for teams that need open-weight portability.
The safest Llama 4 Maverick vs Llama 4 Scout default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Llama 4 Maverick is the strongest answer here for Llama 4 Maverick vs Llama 4 Scout — pick it when quality of output matters more than the $0.60/1M/1M input you pay for it.
Llama 4 Scout handles the same job for about 23% less per token. Start here and only move up if the output is not good enough.
Llama 4 Maverick is the fastest of these for Llama 4 Maverick vs Llama 4 Scout — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Llama 4 Maverick leads on coding with a score of 58 vs 54 for Llama 4 Scout.
Llama 4 Scout has the larger context window: 512K vs 256K for Llama 4 Maverick.
Llama 4 Scout is cheaper at $0.5/1M input tokens vs $0.6/1M for Llama 4 Maverick.
Go with Llama 4 Maverick if you want one model to handle writing and research — it targets flexible self-hosted deployments and mixed general workloads.
Switch to Llama 4 Scout when your work is mostly affordable self-hosted long-context workflows and analysis pipelines; on that narrower brief it is the better tool.
Llama 4 Scout is the more cost-efficient option at $0.5/1M input — Llama 4 Maverick costs 1x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.
Switch the scoring lens to see whether the Llama 4 Maverick vs Llama 4 Scout answer changes when cost, speed, or long-document depth leads the decision.
Meta / Budget / Sep 3, 2026
Best open-weight long-context option for self-hosted pipelines.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You want a hosted solution — Gemini 3.1 Flash gives more context for roughly the same cost.
Where the Llama 4 Maverick vs Llama 4 Scout recommendation shifts once you weigh price or latency differently.
Best flexible option for teams that need open-weight portability.
Best open-weight long-context option for self-hosted pipelines.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Llama 4 MaverickMeta | $0.60/1M | $1.60/1M | $9.20 | 256k tokens | Fast | 58 | 66 | 64 |
| Llama 4 ScoutMeta | $0.50/1M | $1.20/1M | $7.40 | 512k tokens | Fast | 54 | 60 | 78 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for Llama 4 Maverick vs Llama 4 Scout, what it is genuinely good at, and where we would steer you away from it.
Our pick for Llama 4 Maverick vs Llama 4 Scout. It scores 66/100 on the writing axis we weight this page by, and nothing else in this shortlist matches it on output quality.
Flexible open-weight model for teams that want control, portability, and solid general-purpose performance.
You want the strongest hosted answer quality — closed frontier models win on benchmarks.
Best when infrastructure control and open-weight flexibility matter more than absolute peak quality.
Full pricing, benchmark table and release notes on the Llama 4 Maverick page.
The cost-conscious pick for Llama 4 Maverick vs Llama 4 Scout, about 23% less per token than Llama 4 Maverick than the top choice while holding 60/100 on writing.
Long-window open-weight model that handles large document sets at a low price point.
You want a hosted solution — Gemini 3.1 Flash gives more context for roughly the same cost.
A compelling pick for self-hosted long-context pipelines — but Gemini 3.1 Flash now offers 1M context hosted at a similar price.
Full pricing, benchmark table and release notes on the Llama 4 Scout page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Llama 4 Maverick wins on more of the categories we score — writing, research, budget — so it is the better default of the two. Llama 4 Scout is the better pick when your work is mostly affordable self-hosted long-context workflows and analysis pipelines. Neither is universally "better": Llama 4 Maverick is aimed at flexible self-hosted deployments and mixed general workloads, Llama 4 Scout at affordable self-hosted long-context workflows and analysis pipelines.
Llama 4 Scout is cheaper at $0.5/1M input and $1.2/1M output. Llama 4 Maverick costs $0.6/1M input and $1.6/1M output.
Llama 4 Scout has the larger context window at 512K tokens vs Llama 4 Maverick's 256K. For large document analysis, Llama 4 Scout is the stronger pick.
Llama 4 Maverick is better for coding with a score of 58 vs Llama 4 Scout's 54 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
Both Llama 4 Maverick and Llama 4 Scout have similar speed profiles — rated fast. Neither will be the bottleneck if latency is your deciding factor.
Quality depends heavily on deployment setup and hardware. No significant lead over hosted models in any single benchmark category. Avoid it if you want the strongest hosted answer quality — closed frontier models win on benchmarks. That is the main case for looking at Llama 4 Scout instead.
Less polished than hosted frontier models on nuanced tasks. Gemini 3.1 Flash now offers 1M context at only $0.50/1M — bigger and hosted. Avoid it if you want a hosted solution — Gemini 3.1 Flash gives more context for roughly the same cost. Against Llama 4 Maverick specifically, the gap shows up most on coding (58 vs 54).
Take a moderate workload of 10M input and 2M output tokens a month. Llama 4 Maverick runs $9.20 (at $0.6/1M in and $1.6/1M out); Llama 4 Scout runs $7.40 (at $0.5/1M in and $1.2/1M out). That is a $1.80/month difference — Llama 4 Scout is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is Llama 4 Maverick for flexible self-hosted deployments and mixed general workloads, with Llama 4 Scout handling affordable self-hosted long-context workflows and analysis pipelines. Routing high-volume, low-stakes calls to Llama 4 Scout at $0.5/1M and reserving Llama 4 Maverick for the hard cases is usually the cheapest arrangement that does not cost you quality.