Data as of 2026-09-20.
Price spread

Magistral Small

mistralai/magistral-small-2506

Mistral AI· 128K ctx
open weightstool callreasoning quant: unknown

spread (output, p90 ÷ p10)

— too few providers

$1.50 – $1.50 · 2 providers · max÷min 1.0×

2 providers priced · 2 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.NET
inference host
$0.50$1.50$0.25$0.51
Mistralfirst-party
first-party lab
$0.50$1.50—$0.59no cache price published
Pioneer
unclassified
$0.50$1.50$0.50$0.63
Free tiers (rate-limited) · 1

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

  • Nvidia mistralai/magistral-small-2506NVIDIA developer account + API keyfree tier

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