# Meta 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).

## Specifications

| | Meta Llama 3.2 1B Instruct | Ox Alpha |
| --- | --- | --- |
| Lab | Meta | Stealth |
| Access | Open weights | API only |
| Context window | 128K tokens | 1M tokens |
| List price, input | $0.06 / M tokens | $0 / M tokens |
| List price, output | $0.06 / M tokens | $0 / M tokens |
| Cached input | n/a | n/a |
| License | Llama community | Proprietary API |
| Fine-tunable | Yes | No |

Specifications 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.

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[HTML page](https://allocate.network/compare/meta-llama-3-2-1b-instruct-vs-stealth-ox-alpha) · [Meta Llama 3.2 1B Instruct](https://allocate.network/models/meta-llama-3-2-1b-instruct.md) · [Ox Alpha](https://allocate.network/models/stealth-ox-alpha.md) · [Machine-readable catalog](https://allocate.network/catalog.json)