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.
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.
Choose Meta Llama 3.2 1B Instruct for
- Training toward a model you own
Choose Meta Llama 3.2 3B Instruct for
- Training toward a model you own
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.