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Estimate

Together AI Fine-tuning costs $0.48 to $8 per per 1M tokens as of July 2026, with 3 plans available. Pricing depends on your chosen tier, contract length, and negotiated discounts.

Use the interactive pricing calculator to estimate your exact cost based on team size and requirements.

  • Free tier: No free tier available

Together AI Fine-tuning offers 3 pricing tiers: Small Models (Up to 16B), Mid-Size Models (17B–69B), Large Models (70B–100B). The Mid-Size Models (17B–69B) plan is fine-tuning mid-size open-source models (17b–69b).

Last verified: | Sources: 1 pricing pages and reviews
Know Before You Buy — See Together AI Fine-tuning Plans

Together AI Fine-tuning lists $0.48-$8/per 1M tokens, but hidden costs like implementation and support add to the total as of July 2026. Key hidden costs: hosting fine-tuned model endpoint, lora sft training, full fine-tuning. Verified from 1 sources by CostBench.

Hidden Costs Breakdown

1

Hosting Fine-tuned Model Endpoint

high addon

Maintaining the fine-tuned model for inference incurs a substantial recurring charge on a dedicated endpoint, separate from the fine-tuning job cost.

industry

The most significant "hidden" or easily underestimated cost for Together AI Fine-tuning is the hosting of the fine-tuned model on a dedicated endpoint

2

LoRA SFT Training

low implementation

LoRA Supervised Fine-Tuning (SFT) for models up to 16B parameters is priced at $0.48 per million tokens.

industry

LoRA (Low-Rank Adaptation) Supervised Fine-Tuning (SFT) for models up to 16B parameters is priced at $0.48 per million tokens

3

Full Fine-Tuning

low implementation

Full Fine-Tuning costs $0.54 per million tokens.

industry

Other costs include: * Training Costs: Together AI bills fine-tuning per million tokens of training data, with rates varying based on model size, training method, and training type

4

Data Preparation

high implementation

Data preparation includes tasks such as data collection infrastructure, cleaning, annotation, labeling, and quality assurance.

industry

Overall, data acquisition and preparation can account for 30-40% of the total fine-tuning cost

5

Model Hosting

critical overage

This is the ongoing expense of hosting the fine-tuned model on a dedicated endpoint, regardless of actual usage.

industry

While training a LoRA on a 16B base model might cost under a dollar per million training tokens, keeping that model alive on a single H100 GPU around the clock can be approximately $4,700 per month, regardless of actual usage

6

Engineering Time

medium implementation

Significant engineering effort is required for tasks like wiring inference, retrieval, retries, and building user interfaces.

industry

Engineering Time: Significant engineering effort is required for tasks like wiring inference, retrieval, retries, and building user interfaces, which contributes to the overall implementation cost

7

Experimentation Costs

medium overage

Broad testing across multiple models can quickly accumulate costs, even for modest production usage.

industry

Experimentation Costs: Broad testing across multiple models can quickly accumulate costs, even for modest production usage

8

Storage, Retention, and Egress Fees

low overage

Users are advised to confirm the current policy regarding these potential charges in their account and contract terms.

industry

Storage, Retention, and Egress Fees: Users are advised to confirm the current policy regarding these potential charges in their account and contract terms

9

Dedicated Endpoint Hosting

critical addon

After training, fine-tuned models are served on dedicated endpoints, billed per minute based on the hardware attached, regardless of actual inference requests.

industry

Dedicated Endpoint Hosting: After training, fine-tuned models are served on dedicated endpoints, billed per minute based on the hardware attached.

10

Talent Investment

high implementation

This involves the cost of specialized personnel such as ML engineers and data scientists required for fine-tuning projects.

industry

While the fine-tuning job itself is billed per token processed, hosting is a separate, ongoing charge.

11

Data Storage

low addon

Clusters come with Weka or VAST parallel filesystems attached.

industry

Data Storage: Clusters come with Weka or VAST parallel filesystems attached at $0.16/GiB/month with zero egress fees.

Frequently Asked Questions

01 What hidden costs should I budget for with Together AI Fine-tuning?

Beyond the license fee, budget for: Hosting Fine-tuned Model Endpoint ($4,700 per month); LoRA SFT Training ($0.48 per million tokens); Full Fine-Tuning ($0.54 per million tokens); Data Preparation ($3,000 to $8,000 of labor equivalent); Model Hosting ($4,700 per month); Dedicated Endpoint Hosting ($4,700 per month); Talent Investment ($150,000-$250,000 annual salary); Data Storage ($0.16/GiB/month). Exact totals depend on your deployment size and negotiated terms.

02 Does Together AI Fine-tuning charge for implementation?

Together AI Fine-tuning implementation is not included in the license cost. LoRA Supervised Fine-Tuning (SFT) for models up to 16B parameters is priced at $0.48 per million tokens. Estimated impact: $0.48 per million tokens.

03 How much does Together AI Fine-tuning support cost?

Premium support pricing for Together AI Fine-tuning depends on your tier and contract terms. See the sourced cost breakdown above for any verified figures we have.

04 Are there overage or storage costs with Together AI Fine-tuning?

This is the ongoing expense of hosting the fine-tuned model on a dedicated endpoint, regardless of actual usage.. Estimated impact: $4,700 per month.

05 What add-ons cost extra with Together AI Fine-tuning?

Add-on pricing for Together AI Fine-tuning varies by feature. The sourced cost breakdown above lists any verified add-on costs we have.

Now You Know the Real Cost — See Together AI Fine-tuning Plans

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Prices and terms change; verify against the live pricing page.

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