Data as of 2026-09-20.
Price spread

Llama3 3 70B

meta-llama/llama3-3-70b

Meta· 131K ctx
open weightstool call quant: unknown

spread (output, p90 ÷ p10)

— too few providers

$2.80 – $2.80 · 1 providers · max÷min 1.0×

1 provider priced · 1 offering

Cheapest / median / spread use providers that serve the model on their own capacity: first-party lab, hyperscaler, inference host.

Provider classes in the stats:
Blended $/M assumptions

blended = 90.9% input × [(1 − 70% cache) × input + 70% cache × cache-read] + 9.1% × output + cache writes (30% of uncached input) where a write price is published

A provider that publishes no cache price is blended with cache share 0 (all input at the input price) and labelled “no cache price published” — never penalised against identical in/out prices.

ProviderInputOutputCache rdBlended
NanoGPT
router / aggregator
$1.75$2.75$1.75$1.84
Venice AI
inference host
$0.70$2.80—$0.89no cache price published

Data: models.dev (MIT), snapshot 2026-09-20. Prices are vendor-published; verify before purchase. Methodology.