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o4 vs Llama 4 Scout

OpenAI vs Meta. Specs, benchmarks, and real per-task cost — all in one page.

Verdict

Llama 4 Scout is ~56.8× cheaper on a 3:1 input:output blend. Llama 4 Scout is open-weights, the other is proprietary.

OpenAI

Deep-reasoning model. Spends more tokens thinking to crush math, science, and hard coding problems.

State-of-the-art math and scienceExtremely high-ceiling reasoning

Meta

The 70B workhorse open-weight. Fits on a single H100, beloved by self-hosters.

Single-GPU deployableDirt cheap on aggregatorsStrong fine-tuning base

Pricing

Input / 1M$15.00$0.35

Output / 1M$60.00$0.80

Context200K128K

Max output100K8K

LicenseProprietaryOpen weights

Released2026-02-182025-12-10

Benchmarks

LMSYS ELO—1265.0

MMLU Pro93.877.2

HumanEval92.382.4

SWE-Bench68.0—

MATH96.272.5

GPQA82.5—

IFEval—84.1

Per-task cost

Summarize a 1-hour meeting transcript$0.255$0.0057

Review a 500-line pull request$0.240$0.0044

Answer a customer support ticket$0.093$0.0017

Extract structured data from a resume$0.135$0.0026

Debug a stack trace with context$0.210$0.0037

Per-call cost using published token counts for each task. Real-world prompts vary.

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