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Llama 4 Scout vs GPT-5 Mini

Meta AIOpenAIboth via one key, provider price + 3%

Llama 4 Scout (Meta, released April 2025) and GPT-5 Mini (OpenAI, released August 2025) sit at opposite ends of the same budget-tier decision: both are cheap, non-flagship models, but they're built for different jobs. Scout is a mixture-of-experts model tuned for huge context windows and low cost. GPT-5 Mini is a reasoning-enabled compact model tuned for coding and structured output quality. The gap shows up clearly in both pricing and Design Arena benchmarks.

Spec vs spec

SpecLlama 4 ScoutGPT-5 Mini
Context window10M400K
Max output16K128K
Input modalitiestext, imagetext, image, file
Output modalitiestexttext
Knowledge cutoffAug 31, 2024May 31, 2024
ReleasedApr 5, 2025Aug 7, 2025
Reasoningalways on

Pricing

Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.

openkey.ai

meta-llama/llama-4-scout

Input · 1M tokens

$0.100 + 3%$0.103

Output · 1M tokens

$0.300 + 3%$0.309

FEE — FLAT, EVERY MODEL3%

openkey.ai

openai/gpt-5-mini

Input · 1M tokens

$0.250 + 3%$0.258

Output · 1M tokens

$2.00 + 3%$2.06

Cache read · 1M tokens

$0.025 + 3%$0.026

FEE — FLAT, EVERY MODEL3%

One workload, priced on both

10M input + 2M output tokens at each model's price, flat 3% fee included.

meta-llama/llama-4-scoutCheaper

$1.65

$1.60 provider + 3%

openai/gpt-5-mini

$6.70

$6.50 provider + 3%

Benchmarks

Design Arena categories where both models have results. Higher Elo and lower rank win.

Llama 4 ScoutGPT-5 Mini
CategoryEloRankEloRank
Code839#1061164#64
Data viz940#961167#62
Game dev838#1051194#54
UI components824#1001161#57
Websites793#1121167#62

Head-to-head preference voting. How we filter and rank

Pricing math

Provider list price for Llama 4 Scout is $0.10/M input and $0.30/M output; on OpenKey that's $0.103/M and $0.309/M after the flat 3% fee. GPT-5 Mini lists at $0.25/M input and $2.00/M output, which becomes $0.2575/M and $2.06/M on OpenKey. Run a mixed workload of 10M input tokens and 2M output tokens: Scout costs $1.60 total, GPT-5 Mini costs $6.50. That's a 4x cost gap ($6.50 / $1.60), driven almost entirely by output pricing — GPT-5 Mini's completion price is nearly 7x Scout's. GPT-5 Mini also gives you a $0.025/M cache-read discount on repeated prompts; Scout has no caching pricing listed.

Coding and UI benchmarks

Design Arena scores both models on real coding and design tasks, and the gap is consistent across every category they share. In codecategories, GPT-5 Mini scores 1164 Elo (rank 64) versus Scout's 839 (rank 106) — a 325-point gap. In dataviz, GPT-5 Mini leads 1167 to 940 (227 points). In gamedev, 1194 to 838 (356 points). In uicomponent, 1161 to 824 (337 points). In website, 1167 to 793 (374 points) — Scout's weakest category. GPT-5 Mini also has scores in categories Scout doesn't compete in (3d: 1114, asciiart: 1173, svg: 1149), suggesting broader coverage of front-end and generative tasks.

Context and long-document work

Scout's context window is 10,000,000 tokens against GPT-5 Mini's 400,000 — a 25x ratio. If your job is ingesting large codebases, log dumps, or multi-document corpora in a single call, Scout is the only one of the two that fits without chunking. GPT-5 Mini's max output is larger, though: 128,000 tokens versus Scout's 16,384, so for tasks that generate long structured output (long reports, large code files) in one pass, GPT-5 Mini has more room on the output side even with a smaller input window.

Modality and reasoning differences

Both models accept text and image input; GPT-5 Mini also accepts file input directly, which Scout does not list. GPT-5 Mini has mandatory reasoning with four effort levels (high, medium, low, minimal — default medium), which adds latency but is what drives its coding advantage. Scout has no reasoning parameter — it's a straight instruct model, which makes it faster for simple extraction or classification tasks where reasoning overhead isn't worth paying for. Knowledge cutoffs differ too: Scout's is 2024-08-31, three months newer than GPT-5 Mini's 2024-05-31.

Which model for which job

Use casePickWhy
Large codebase analysis (multi-file, single call)Llama 4 Scout10M token context vs 400K — fits far more code in one request
Coding assistant / code generation qualityGPT-5 MiniLeads Scout by 325 Elo points on Design Arena codecategories
High-volume, cost-sensitive batch jobsLlama 4 Scout$1.60 vs $6.50 for a 10M-in/2M-out workload
UI component or website generationGPT-5 Mini337 and 374-point Elo leads on uicomponent and website categories
Long single-pass output (reports, large files)GPT-5 Mini128,000 max output tokens vs Scout's 16,384
File-based input (PDFs, documents)GPT-5 MiniSupports file as an input modality; Scout only lists text and image

Questions

How much more does GPT-5 Mini cost than Llama 4 Scout?
On a 10M input / 2M output token workload, GPT-5 Mini costs $6.50 on OpenKey versus $1.60 for Llama 4 Scout — about 4x more. The gap comes mostly from output pricing: $2.06/M for GPT-5 Mini versus $0.309/M for Scout, both OpenKey prices after the flat 3% fee on provider list.
Which model has a bigger context window?
Llama 4 Scout supports 10,000,000 tokens of context, 25 times larger than GPT-5 Mini's 400,000. If you need to process very large documents or codebases in a single call, Scout is the only option of the two.
Is GPT-5 Mini actually better at coding?
Yes, by a clear margin on Design Arena: it beats Scout by 325 Elo points in codecategories (1164 vs 839), 337 in uicomponent, and 374 in website generation. Scout's smallest gap is in dataviz, where it still trails by 227 points.
Can I use both models with the same API key?
Yes — both Llama 4 Scout and GPT-5 Mini are available on OpenKey with one API key across all 329 models, and pricing is provider list price plus a flat 3% fee, so you can switch between them per request without separate accounts.

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