Data as of 2026-09-20.
Price spread

Llama 4 Maverick 17B 128e Instruct

meta-llama/llama-4-maverick-17b-128e-instruct

Meta· 131K ctx
open weightstool call quant: unknown

spread (output, p90 ÷ p10)

1.3×

$0.600 – $1.48 · 6 providers · max÷min 2.5×

6 providers priced · 6 offerings

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
IO.NETfp8
inference host
$0.150$0.600$0.0750$0.168
Deep Infrafp8
inference host
$0.200$0.800—$0.255no cache price published
NovitaAIfp8
inference host
$0.270$0.850—$0.323no cache price published
Azurefp8
hyperscaler
$0.25$1.00—$0.32no cache price published
Azure Cognitive Servicesfp8
hyperscaler
$0.25$1.00—$0.32no cache price published
watsonx.aifp8outlier
hyperscaler
$0.37$1.48—$0.47no cache price published
Free tiers (rate-limited) · 1

No payment required; rate limits and quotas apply (not tracked yet). Excluded from cheapest, median and spread.

  • Nvidia meta/llama-4-maverick-17b-128e-instructNVIDIA developer account + API keyfree tier
Unpriced · 1

Listed at $0 with no published pricing — we can't tell whether it's free, bundled or just missing. Excluded from cheapest, median and spread.

  • Llama llama-4-maverick-17b-128e-instruct-fp8unpriced

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