Data story · provider

Together AI: model lineup and pricing overview

Together AI model lineup with prices, context windows and average benchmark scores. Inference and training cloud for open models.

What the data shows

Together AI has 14 models in the index. The average input price is $2.28 and the average output price is $10.11 per million tokens.

The strongest model by average score is llama-3-1-turbo. The cheapest by input price is Mixtral Turbo 1.5B.

How to read the lineup

  • Start with the best model for quality-sensitive work.
  • Use the cheapest model for high-volume tasks.
  • Check open-weight availability if self-hosting matters.
  • Keep a second provider for fallback.

Together AI models

#ModelInput / 1MOutput / 1MContextAvg score
1Llama 3.1 Turbo$4.17$21.10200,00076.8
2Llama 3.1 Turbo Instruct$4.21$17.7332,76876.7
3Llama 3.1 Turbo Chat$3.95$20.39200,00076.1
4Llama 3.1 Turbo Base$3.30$13.5916,38473.0
5Mixtral Turbo$3.20$13.6665,53672.4
6Mixtral Turbo Instruct$3.16$13.0432,76871.9
7Mixtral Turbo Chat$3.02$11.8032,76871.7
8Mixtral Turbo Base$2.53$10.8032,76869.7
9Llama 3.1 Turbo 8B$1.16$5.4832,76858.8
10Llama 3.1 Turbo 7B$0.98$4.148,19256.4
11Mixtral Turbo 8B$0.75$3.514,09654.1
12Mixtral Turbo 7B$0.68$2.868,19253.2
13Llama 3.1 Turbo 1.5B$0.46$2.2416,38449.8
14Mixtral Turbo 1.5B$0.31$1.194,09647.6

Methodology

This story uses the AI & LLM Index dataset: 600 models, 40 providers and 12 benchmarks. Prices are listed per million tokens. Scores are modelled estimates on a 0–100 scale and are not official benchmark results. Figures are rounded for readability.

Related

FAQ

What does the Together AI: model lineup and pricing overview data show?

Together AI model lineup with prices, context windows and average benchmark scores. Inference and training cloud for open models.

Are the numbers official?

No. Prices and scores are compiled for this demo index. Benchmark values are modelled estimates, not official results. Verify figures with the provider or benchmark owner before making decisions.

How should I use this ranking?

Use it to form a shortlist. Check the specific model pages, compare price and context, and test the shortlist on your own examples before committing.