Comparisons

Meta Llama 3.2 1B Instruct vs Meta Llama 3.2 3B Instruct

On provider list prices, Meta Llama 3.2 1B Instruct costs $0.06 per million input tokens against $0.06 for Meta Llama 3.2 3B Instruct: effectively level. Output is $0.06 against $0.06. On Allocate both bill at list plus the 7% transaction fee.

Meta Llama 3.2 1B Instruct Meta Llama 3.2 3B Instruct
LabMetaMeta
AccessOpen weightsOpen weights
Context window128K tokens128K tokens
List price, input$0.06 / M tokens$0.06 / M tokens
List price, output$0.06 / M tokens$0.06 / M tokens
Cached inputn/an/a
LicenseLlama communityLlama community
Fine-tunableYesYes

Specifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.

What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $93 a month on Meta Llama 3.2 1B Instruct and $93 on Meta Llama 3.2 3B Instruct at list: a gap of $0.

Meta Llama 3.2 1B Instruct$0.06$0.06
Meta Llama 3.2 3B Instruct$0.06$0.06
InputOutput

Choose Meta Llama 3.2 1B Instruct for

  • Training toward a model you own
Meta Llama 3.2 1B Instruct details

Choose Meta Llama 3.2 3B Instruct for

  • Training toward a model you own
Meta Llama 3.2 3B Instruct details

Common questions

Which is cheaper, Meta Llama 3.2 1B Instruct or Meta Llama 3.2 3B Instruct?

Meta Llama 3.2 1B Instruct, on this workload shape. At list prices it is $0.06/$0.06 per million tokens in and out against $0.06/$0.06 for Meta Llama 3.2 3B Instruct. Billed on Allocate: $0.064/$0.064 against $0.064/$0.064, list plus 7%.

Which has the bigger context window?

They match: both read 131,072 tokens (128K) per request.

Can I fine-tune Meta Llama 3.2 1B Instruct or Meta Llama 3.2 3B Instruct?

Both publish open weights (Meta Llama 3.2 1B Instruct: Llama community; Meta Llama 3.2 3B Instruct: Llama community), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

Related comparisons

Run the numbers on your workload

Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.