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o4 vs Llama 4 Behemoth

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

Verdict

Llama 4 Behemoth is ~6.8× cheaper on a 3:1 input:output blend. Llama 4 Behemoth 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

Meta’s open-weights flagship. 405B params, fully open license, runs on every major inference provider.

Best open-weights modelRuns anywhereTransparent training

Pricing

Input / 1M$15.00$2.50

Output / 1M$60.00$8.00

Context200K256K

Max output100K16K

LicenseProprietaryOpen weights

Released2026-02-182025-12-10

Benchmarks

LMSYS ELO—1342.0

MMLU Pro93.887.1

HumanEval92.389.3

SWE-Bench68.052.4

MATH96.281.5

GPQA82.556.2

IFEval—88.0

Per-task cost

Summarize a 1-hour meeting transcript$0.255$0.041

Review a 500-line pull request$0.240$0.036

Answer a customer support ticket$0.093$0.014

Extract structured data from a resume$0.135$0.021

Debug a stack trace with context$0.210$0.031

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

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