Data as of 2026-09-20.
Price spread

Llama 4 Maverick 17B Instruct

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

Meta· 1.0M ctx
open weights quant: unknown

spread (output, p90 ÷ p10)

— too few providers

$0.720 – $0.970 · 2 providers · max÷min 1.3×

2 providers priced · 3 offerings · 1 omitted (stale)

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
Abacusfp8
router / aggregator
$0.140$0.590—$0.181no cache price published
OCI Generative AIfp8
hyperscaler
$0.720$0.720—$0.720no cache price published
LLM Gateway
router / aggregator
$0.270$0.850—$0.323no cache price published
Amazon Bedrock
hyperscaler
$0.240$0.970—$0.306no cache price published
Neon
router / aggregator
$0.50$1.50—$0.59no cache price published
Stale offerings (not in the spread) · 1

Last priced more than 3 days before the latest snapshot — shown for reference, never mixed into cheapest, median or spread.

  • Charm Hyper llama-4-maverick-17b-128e-instruct-fp8pay per token
Subscription plans (flat fee, not per-token) · 1

Flat-fee plan — the per-token price is bundled into a subscription, so $0/token is not free. Excluded from cheapest, median and spread.

  • DevPass (LLM Gateway) llama-4-maverick-17b-instructsubscription plan

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