# Meta Llama 3.3 70B Instruct Turbo vs Qwen3.7 Max

On provider list prices, Meta Llama 3.3 70B Instruct Turbo costs $1.04 per million input tokens against $1.25 for Qwen3.7 Max: 1.2x apart. Output is $1.04 against $3.75 (3.6x). On Allocate both bill at list plus the 7% transaction fee.

## Specifications

| | Meta Llama 3.3 70B Instruct Turbo | Qwen3.7 Max |
| --- | --- | --- |
| Lab | Meta | Qwen |
| Access | Open weights | API only |
| Context window | 128K tokens | 1M tokens |
| List price, input | $1.04 / M tokens | $1.25 / M tokens |
| List price, output | $1.04 / M tokens | $3.75 / M tokens |
| Cached input | n/a | $0.13 / M tokens |
| License | Llama community | Proprietary API |
| Fine-tunable | Yes | No |

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 $2,813 on Qwen3.7 Max at list: a gap of $1,201, or 1.7x.

Qwen3.7 Max 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 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

## Choose Qwen3.7 Max for

- The longer context window (1M vs 128K tokens)
- Published cached-input pricing ($0.13 per M tokens)

## Common questions

### Which is cheaper, Meta Llama 3.3 70B Instruct Turbo or Qwen3.7 Max?

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 $1.25/$3.75 for Qwen3.7 Max. Billed on Allocate: $1.11/$1.11 against $1.34/$4.01, list plus 7%.

### Which has the bigger context window?

Qwen3.7 Max: 1,000,000 tokens (1M) against 131,072 (128K) for Meta Llama 3.3 70B Instruct Turbo.

### Can I fine-tune Meta Llama 3.3 70B Instruct Turbo or Qwen3.7 Max?

Meta Llama 3.3 70B Instruct Turbo publishes open weights (Llama community) and can be fine-tuned on your own data. Qwen3.7 Max is a closed model served over API; its weights are not available.

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[HTML page](https://allocate.network/compare/meta-llama-3-3-70b-instruct-turbo-vs-qwen-qwen3-7-max) · [Meta Llama 3.3 70B Instruct Turbo](https://allocate.network/models/meta-llama-3-3-70b-instruct-turbo.md) · [Qwen3.7 Max](https://allocate.network/models/qwen-qwen3-7-max.md) · [Machine-readable catalog](https://allocate.network/catalog.json)