# Gemini 3.1 Pro vs Meta Llama 3.3 70B Instruct Turbo

On provider list prices, Meta Llama 3.3 70B Instruct Turbo costs $1.04 per million input tokens against $2 for Gemini 3.1 Pro: 1.9x apart. Output is $1.04 against $12 (11.5x). On Allocate both bill at list plus the 7% transaction fee.

## Specifications

| | Gemini 3.1 Pro | Meta Llama 3.3 70B Instruct Turbo |
| --- | --- | --- |
| Lab | Google | Meta |
| Access | API only | Open weights |
| Context window | 1M tokens | 128K tokens |
| List price, input | $2 / M tokens | $1.04 / M tokens |
| List price, output | $12 / M tokens | $1.04 / M tokens |
| Cached input | n/a | n/a |
| License | Proprietary API | Llama community |
| Fine-tunable | No | Yes |

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 $1,612 a month on Meta Llama 3.3 70B Instruct Turbo and $6,600 on Gemini 3.1 Pro at list: a gap of $4,988, or 4.1x.

Gemini 3.1 Pro reads 1M tokens per request against 128K for Meta Llama 3.3 70B Instruct Turbo, 7.6x the window. That decides which one can take whole documents without splitting them.

## Choose Gemini 3.1 Pro for

- Judgment-heavy workflows
- Long-context analysis
- Escalation tier above Flash

## Choose Meta Llama 3.3 70B Instruct Turbo for

- The lower list price ($1.04 in / $1.04 out per M tokens)
- Open weights you can fine-tune and own

## Common questions

### Which is cheaper, Gemini 3.1 Pro or Meta Llama 3.3 70B Instruct Turbo?

Meta Llama 3.3 70B Instruct Turbo, on this workload shape. At list prices it is $1.04/$1.04 per million tokens in and out against $2/$12 for Gemini 3.1 Pro. Billed on Allocate: $1.11/$1.11 against $2.14/$12.84, list plus 7%.

### Which has the bigger context window?

Gemini 3.1 Pro: 1,000,000 tokens (1M) against 131,072 (128K) for Meta Llama 3.3 70B Instruct Turbo.

### Can I fine-tune Gemini 3.1 Pro or Meta Llama 3.3 70B Instruct Turbo?

Meta Llama 3.3 70B Instruct Turbo publishes open weights (Llama community) and can be fine-tuned on your own data. Gemini 3.1 Pro is a closed model served over API; its weights are not available.

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[HTML page](https://allocate.network/compare/google-gemini-3-1-pro-vs-meta-llama-3-3-70b-instruct-turbo) · [Gemini 3.1 Pro](https://allocate.network/models/google-gemini-3-1-pro.md) · [Meta Llama 3.3 70B Instruct Turbo](https://allocate.network/models/meta-llama-3-3-70b-instruct-turbo.md) · [Machine-readable catalog](https://allocate.network/catalog.json)