Data as of 2026-09-20.
Price spread

Mistral Small 3.2 24B Instruct 2506

mistralai/mistral-small-3.2-24b-instruct-2506

Mistral AI· 33K ctx
open weightstool callstructured quant: unknown

spread (output, p90 ÷ p10)

— too few providers

$0.310 – $0.350 · 3 providers · max÷min 1.1×

3 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
OVHcloud AI Endpoints
inference host
$0.100$0.310—$0.119no cache price published
Cortecs
router / aggregator
$0.100$0.312—$0.119no cache price published
Berget.AI
inference host
$0.330$0.330—$0.330no cache price published
Scaleway
inference host
$0.150$0.350—$0.168no 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.

  • NanoGPT chutesai/Mistral-Small-3.2-24B-Instruct-2506pay per token
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.

  • Meganova mistralai/Mistral-Small-3.2-24B-Instruct-2506unpriced

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