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Head-to-head comparison

Llama 3.2 1B Instruct vs Llama 4 Scout

Llama 3.2 1B Instruct (Meta) and Llama 4 Scout (Meta) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.

Snapshot as of 7 November 2026

As of 7 November 2026, Llama 4 Scout holds the stronger ModelCap Index position (#229 vs #348); Llama 3.2 1B Instruct is 1.5× cheaper per output token ($0.201/1M vs $0.30/1M); and Llama 4 Scout offers the longer context window (1.3M vs 60K tokens).

Which should you choose?

Choose Llama 3.2 1B Instruct if…

  • API cost matters — $0.201/1M output tokens against $0.30/1M, about 1.5× cheaper.
  • your workload is prompt-heavy — input tokens cost $0.027/1M against $0.10/1M.

Choose Llama 4 Scout if…

  • you want the stronger overall ModelCap Index position — #229 against #348 (31.3 vs 4.6 points).
  • you need the longer context window — 1.3M tokens against 60K.
  • you want provider choice — 2 listed API providers against 1.
  • Arena text is your yardstick — 1322 against 1111.
  • Arena coding is your yardstick — 1362 against 1149.
  • BFCL V4 is your yardstick — 28.1 against 10.8.
  • you want the more recently listed model — Llama 4 Scout was listed 5 April 2025, Llama 3.2 1B Instruct 25 September 2024.

Llama 3.2 1B Instruct vs Llama 4 Scout: specs, pricing and context

Specification comparison of Llama 3.2 1B Instruct and Llama 4 Scout
FieldLlama 3.2 1B InstructMetaLlama 4 ScoutMeta
ModelCap Index position#348#229
Index score4.631.3
EvidenceMeasuredMeasured
Input price / 1M tokens$0.027$0.10
Output price / 1M tokens$0.201$0.30
Context window60K tokens1.3M tokens
Declared route output cap54K16K
API providers listed12
Weight accessGated accessGated access
Input modalitiesTextText, Image
First listed25 September 20245 April 2025
PublisherMetaMeta

Evidence: 2 public benchmark observations across 2 boards · 3 public benchmark observations across 3 boards. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.

Benchmark scores: Llama 3.2 1B Instruct vs Llama 4 Scout

Public benchmark boards where Llama 3.2 1B Instruct or Llama 4 Scout has a published result
BoardLlama 3.2 1B InstructLlama 4 ScoutLeads
Arena textArena (LMArena)11111103–1119Not reported13221317–1326Not reportedLlama 4 Scout
Arena codingArena (LMArena)11491133–116613621354–1371Llama 4 Scout
ARC-AGI-2ARC Prize Foundation—0.0%Only one result
BFCL V4UC Berkeley (Gorilla)10.8Function calling28.1Function callingLlama 4 Scout

Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.

Want a different pairing? Open the interactive comparison tool to swap either model for any current ranked language model.

Llama 3.2 1B Instruct vs Llama 4 Scout: common questions

Is Llama 3.2 1B Instruct better than Llama 4 Scout?

Llama 4 Scout ranks higher on the ModelCap Index as of 7 November 2026: #229 against #348. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it. Their published uncertainty intervals do not overlap, but the aggregate Index does not predict performance on every task; compare the relevant benchmark configurations before choosing.

Is Llama 3.2 1B Instruct cheaper than Llama 4 Scout?

Llama 3.2 1B Instruct is cheaper on output tokens: $0.201/1M against $0.30/1M. Input tokens are $0.027/1M for Llama 3.2 1B Instruct and $0.10/1M for Llama 4 Scout. Prices are the lowest listed API offer ModelCap observed, in USD per million tokens. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.15 for Llama 3.2 1B Instruct versus $0.35 for Llama 4 Scout. Llama 3.2 1B Instruct costs 55.9% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.

Which has the bigger context window, Llama 3.2 1B Instruct or Llama 4 Scout?

Llama 4 Scout has the larger context window: 1.3M tokens against 60K. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified.

Which is better for coding, Llama 3.2 1B Instruct or Llama 4 Scout?

Arena coding: Llama 3.2 1B Instruct 1149, Llama 4 Scout 1362 — Llama 4 Scout leads.

Are Llama 3.2 1B Instruct and Llama 4 Scout open-weight models?

Llama 3.2 1B Instruct: Gated access. Llama 4 Scout: Gated access. Open weights mean the checkpoint can be downloaded and self-hosted under its licence. A missing weight link does not identify every API or chat product that offers a model.

Where can I run Llama 3.2 1B Instruct and Llama 4 Scout?

ModelCap currently lists 1 API provider for Llama 3.2 1B Instruct and 2 for Llama 4 Scout, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.

How current is this Llama 3.2 1B Instruct vs Llama 4 Scout comparison?

Every figure and ModelCap Index position comes from the same published snapshot dated 7 November 2026. Publication and page updates happen separately; use the snapshot date shown on the page.

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