GPT-5.2 Mini wins on coding (78 vs 54) and writing quality. Llama 4 Scout wins on price ($0.5 vs $1.2/1M input) and context window (512K vs 128K). For most workflows, GPT-5.2 Mini is the stronger default — solid openai budget option, though gemini flash offers better value.
The safest GPT-5.2 Mini vs Llama 4 Scout default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-5.2 Mini is the strongest answer here for GPT-5.2 Mini vs Llama 4 Scout — pick it when quality of output matters more than the $1.20/1M/1M input you pay for it.
Llama 4 Scout handles the same job for about 72% less per token. Start here and only move up if the output is not good enough.
GPT-5.2 Mini is the fastest of these for GPT-5.2 Mini vs Llama 4 Scout — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-5.2 Mini leads on coding with a score of 78 vs 54 for Llama 4 Scout.
Llama 4 Scout has the larger context window: 512K vs 128K for GPT-5.2 Mini.
Llama 4 Scout is cheaper at $0.5/1M input tokens vs $1.2/1M for GPT-5.2 Mini.
Choose GPT-5.2 Mini for budget technical workflows and high-volume product integrations. Its coding and budget scores are what carry the recommendation here.
Choose Llama 4 Scout when your work is mostly affordable self-hosted long-context workflows and analysis pipelines — that is the workload it was tuned for.
Llama 4 Scout is the more cost-efficient option at $0.5/1M input — GPT-5.2 Mini costs 2x 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 GPT-5.2 Mini vs Llama 4 Scout answer changes when cost, speed, or long-document depth leads the decision.
OpenAI / Balanced / Mar 24, 2026
Solid OpenAI budget option, though Gemini Flash offers better value.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Cost is your primary concern — Gemini 3.1 Flash offers more for less.
Where the GPT-5.2 Mini vs Llama 4 Scout recommendation shifts once you weigh price or latency differently.
Solid OpenAI budget option, though Gemini Flash offers better value.
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 |
|---|---|---|---|---|---|---|---|---|
| GPT-5.2 MiniOpenAI | $1.20/1M | $4.80/1M | $22 | 128k tokens | Fast | 78 | 72 | 68 |
| 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 GPT-5.2 Mini vs Llama 4 Scout, what it is genuinely good at, and where we would steer you away from it.
The default answer for GPT-5.2 Mini vs Llama 4 Scout — 78/100 on the coding axis, and the model we would start with unless the price below rules it out.
Lower-cost OpenAI model that keeps a solid balance of usefulness, speed, and affordability for everyday tasks.
Cost is your primary concern — Gemini 3.1 Flash offers more for less.
A decent budget OpenAI pick, but Gemini 3.1 Flash undercuts it on price with a larger context window.
Full pricing, benchmark table and release notes on the GPT-5.2 Mini page.
The value option for GPT-5.2 Mini vs Llama 4 Scout: about 72% less per token than GPT-5.2 Mini, at 54/100 on coding. Worth starting here and moving up only if the output disappoints.
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.
Newsletter
We email when the GPT-5.2 Mini vs Llama 4 Scout pick changes, when one of these models moves on price, or when something new displaces the current leader.
No spam. Useful updates only. Affiliate disclosures always clearly labeled.
GPT-5.2 Mini wins on more of the categories we score — coding, budget, writing — 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": GPT-5.2 Mini is aimed at budget technical workflows and high-volume product integrations, 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. GPT-5.2 Mini costs $1.2/1M input and $4.8/1M output.
Llama 4 Scout has the larger context window at 512K tokens vs GPT-5.2 Mini's 128K. For large document analysis, Llama 4 Scout is the stronger pick.
GPT-5.2 Mini is better for coding with a score of 78 vs Llama 4 Scout's 54 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
Both GPT-5.2 Mini and Llama 4 Scout have similar speed profiles — rated fast. Neither will be the bottleneck if latency is your deciding factor.
Weaker on nuanced reasoning than premium models. Gemini 3.1 Flash is now cheaper with a larger context window. Avoid it if cost is your primary concern — Gemini 3.1 Flash offers more for less. 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 GPT-5.2 Mini specifically, the gap shows up most on coding (78 vs 54).
Take a moderate workload of 10M input and 2M output tokens a month. GPT-5.2 Mini runs $21.60 (at $1.2/1M in and $4.8/1M out); Llama 4 Scout runs $7.40 (at $0.5/1M in and $1.2/1M out). That is a $14.20/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 GPT-5.2 Mini for budget technical workflows and high-volume product integrations, 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 GPT-5.2 Mini for the hard cases is usually the cheapest arrangement that does not cost you quality.