AllocateMeta Llama 3.2 1B Instruct vs Ox Alpha
On provider list prices, Ox Alpha costs $0 per million input tokens against $0.06 for Meta Llama 3.2 1B Instruct: 600.0x apart. Output is $0 against $0.06 (600.0x).
Meta Llama 3.2 1B InstructO Ox AlphaSpecifications and provider list prices from the Allocate catalog, checked 2026-07-21.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $0 a month on Ox Alpha and $93 on Meta Llama 3.2 1B Instruct at list: a gap of $93, or Infinityx.
Ox Alpha reads 1M tokens per request against 128K for Meta Llama 3.2 1B Instruct, 8.0x the window. That decides which one can take whole documents without splitting them.
Choose Meta Llama 3.2 1B Instruct for
- Open weights you can fine-tune and own
Choose Ox Alpha for
- The lower list price ($0 in / $0 out per M tokens)
- The longer context window (1M vs 128K tokens)
Common questions
Which is cheaper, Meta Llama 3.2 1B Instruct or Ox Alpha?
Ox Alpha, on this workload shape. At list prices it is $0/$0 per million tokens in and out against $0.06/$0.06 for Meta Llama 3.2 1B Instruct. Billed on Allocate: $0/$0 against $0.064/$0.064.
Which has the bigger context window?
Ox Alpha: 1,048,576 tokens (1M) against 131,072 (128K) for Meta Llama 3.2 1B Instruct.
Can I fine-tune Meta Llama 3.2 1B Instruct or Ox Alpha?
Meta Llama 3.2 1B Instruct publishes open weights (Llama community) and can be fine-tuned on your own data. Ox Alpha is a closed model served over API; its weights are not available.
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.