# Trinity Mini vs Meta Llama 3.2 1B Instruct

On provider list prices, Meta Llama 3.2 1B Instruct costs $0.06 per million input tokens against $0.045 for Trinity Mini: effectively level. Output is $0.06 against $0.15 (2.5x).

## Specifications

| | Trinity Mini | Meta Llama 3.2 1B Instruct |
| --- | --- | --- |
| Lab | Arcee AI | Meta |
| Access | Open weights | Open weights |
| Context window | 128K tokens | 128K tokens |
| List price, input | $0.045 / M tokens | $0.06 / M tokens |
| List price, output | $0.15 / M tokens | $0.06 / M tokens |
| Cached input | n/a | n/a |
| License | Not listed | Llama community |
| Fine-tunable | Yes | Yes |

Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.

## 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 $106.50 on Trinity Mini at list: a gap of $13.50.

Meta Llama 3.2 1B Instruct reads 128K tokens per request against 128K for Trinity Mini, 1.0x the window. That decides which one can take whole documents without splitting them.

## Choose Trinity Mini for

- The lower list price ($0.045 in / $0.15 out per M tokens)

## Choose Meta Llama 3.2 1B Instruct for

- The longer context window (128K vs 128K tokens)

## Common questions

### Which is cheaper, Trinity Mini or Meta Llama 3.2 1B 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 $0.045/$0.15 for Trinity Mini. Billed on Allocate: $0.064/$0.064 against $0.048/$0.16.

### Which has the bigger context window?

Meta Llama 3.2 1B Instruct: 131,072 tokens (128K) against 128,000 (128K) for Trinity Mini.

### Can I fine-tune Trinity Mini or Meta Llama 3.2 1B Instruct?

Both publish open weights (Trinity Mini: Not listed; Meta Llama 3.2 1B Instruct: Llama community), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

---

[HTML page](https://allocate.network/compare/arcee-trinity-mini-vs-meta-llama-3-2-1b-instruct) · [Trinity Mini](https://allocate.network/models/arcee-trinity-mini.md) · [Meta Llama 3.2 1B Instruct](https://allocate.network/models/meta-llama-3-2-1b-instruct.md) · [Machine-readable catalog](https://allocate.network/catalog.json)