Pricing

Per-token credits. Public rates. No seats, no minimums.

One credit equals one US dollar of billed compute. Buy credit packs outright or subscribe monthly — the per-token rate is the same. Adapters are always yours to download.

Credit packs

Buy once. Spend whenever.

Larger packs include a volume bonus. Packs never expire.

Starter

10 credits

$10
One-time purchase via Stripe.
Growth

28 credits

$25
bonus +12%
One-time purchase via Stripe.
Professional

60 credits

$50
bonus +20%
One-time purchase via Stripe.
Scale

130 credits

$100
bonus +30%
One-time purchase via Stripe.
Monthly subscriptions

Predictable monthly allowance.

Around 20% more credits per dollar than pay-as-you-go packs, in exchange for a recurring commit. Top up with packs any time.

Starter

Small, steady usage

$29 / mo
35 credits per month.
  • 1 concurrent training job
  • 7-day job history retention
  • Adapter download on every run
  • Top up any time with credit packs
Pro · recommended

Regular fine-tuning cadence

$99 / mo
130 credits per month.
  • 3 concurrent training jobs
  • 30-day job history retention
  • Priority queue placement
  • Top up any time with credit packs
Scale

Teams running many jobs

$299 / mo
420 credits per month.
  • 10 concurrent training jobs
  • 90-day job history retention
  • Dedicated support
  • Top up any time with credit packs
Training rates

Per million training tokens.

You’re billed on every token the trainer sees — rows × context × epochs. Failed runs (pre-training) are fully refunded.

Model sizePrice / 1M tokensCredits / 1M tokens
≤ 3B$0.110.11 cr
7 – 8B$0.590.59 cr
13 – 14B$0.990.99 cr
32B$3.323.32 cr
70B$8.308.30 cr
TYPICAL JOB COSTS
Quick experiment200 rows · 128 tokens · 3 epochs · 3B · ~77K tokens~$0.01
Small fine-tune500 rows · 256 tokens · 3 epochs · 7B · ~384K tokens~$0.23
Medium fine-tune2K rows · 512 tokens · 5 epochs · 7B · ~5.1M tokens~$3.01
Large fine-tune10K rows · 1024 tokens · 3 epochs · 7B · ~30.7M tokens~$18.10
Inference rates

Per million inference tokens.

Billed on prompt_tokens + completion_tokens from each response. Served via vLLM on shared serverless capacity.

Model sizePrice / 1M tokensCredits / 1M tokens
≤ 3B$0.0120.012 cr
7 – 8B$0.0600.060 cr
13 – 14B$0.0990.099 cr
32B$0.3320.332 cr
70B$0.8300.830 cr

Hosted inference launches after the current training-focused alpha. During alpha you can download any adapter and serve it yourself from the first completed run.

FAQ

Questions we hear.

What is one credit?

One credit equals one US dollar of billed compute. Credit packs and subscription allowances are denominated in credits; the billing ledger shows every deduction at per-token granularity.

What's charged if a training run fails?

Nothing, if it fails before the first gradient step (infra error, bad dataset). Reserved credits are refunded in full. If training has already started, GPU time was consumed and credits are not refunded — partial results may still be downloadable.

Do my credits expire?

Credit packs do not expire. Monthly subscription allowances do not roll over — unused credits reset on each renewal.

Can I subscribe and top up with packs at the same time?

Yes. Subscription credits are consumed first each month; pack credits are used after the monthly allowance runs out.

Do my datasets or queries train the OwnLLM base model?

No. Never. Your corpus and inference traffic are never used to train our base models. That's contracted in the DPA, not just promised.

Do I own the adapter I trained?

Yes. Every completed job produces a downloadable adapter you can serve yourself. No lock-in.

What happens if I run out of credits mid-use?

Job submission is rejected with a 402 response. Top up a credit pack or upgrade your subscription and resubmit.

Ready to train your first adapter?