# The headline numbers say it all
When you line up the raw figures, Fireworks AI’s serverless inference is $1 per unit, while Modal’s “Why serverless?” line reads $5400. That contrast forces a quick decision: are you paying for pure compute or for a broader platform experience?
What each vendor actually charges
Fireworks AI offers a minimalist, usage‑based menu: serverless inference $1, managed training $0.5 (which bundles a base model, LoRA SFT, and LoRA DPO), serverless training API $4.86 (with checkpoint storage included during private preview), and on‑demand deployments $0.13 (with a 1.5x premium for region‑restricted deployments). Modal’s catalog looks more like a tiered SaaS offering: a $10 credit grant for academics, a $5400 “Why serverless?” line that likely covers a bundle of compute, storage, and platform services, a Starter plan at $0/month that advertises “compute / month”, a Team tier at $250/month for the same compute bucket, and a second Starter at $30/month that adds custom compute and a workspace.
Where the money goes
Fireworks AI’s model is pure consumption. You pay only when you spin up an inference request or trigger a training job, and the line‑item breakdown tells you exactly what each operation costs. There’s no monthly commitment, no hidden seat fees, and the only premium you see is the optional region surcharge on deployments. This makes it attractive for teams that run intermittent workloads, experiment with new models, or need to keep overhead predictable.
Modal, by contrast, layers monthly subscriptions on top of its usage model. The $0/month Starter suggests a free tier, but the inclusion of “compute / month” without a clear unit leaves you guessing how much actual work you can do before hitting limits. The $250/month Team tier bundles compute for a whole group, which can be cost‑effective if you have a stable, predictable demand. The $30/month Starter with custom compute and a workspace is a middle ground for small teams that need a collaborative environment but don’t want the $5400 “Why serverless?” price tag.
A quick comparison table
| Feature | Fireworks AI | Modal |
|---|---|---|
| Serverless inference | $1 | – |
| Managed training | $0.5 | – |
| Serverless training API | $4.86 | – |
| On‑demand deployments | $0.13 | – |
| Academic credit grant | – | $10 |
| Why serverless? | – | $5400 |
| Starter (free) | – | $0/month (compute / month) |
| Starter (paid) | – | $30/month (custom compute + workspace) |
| Team | – | $250/month (compute / month) |
The right pick for your workflow
If you are a startup or an R&D team that spikes usage and wants to avoid any fixed monthly bill, Fireworks AI’s per‑unit pricing gives you the most transparent cost structure. The ability to pay $0.5 for managed training and $1 for inference means you can scale up or down without renegotiating contracts. On the other hand, if you run a steady‑state service, need a shared workspace, and prefer a predictable monthly invoice, Modal’s Team plan at $250/month may provide the convenience of bundled compute and support, even though the $5400 “Why serverless?” line suggests a premium for enterprise‑grade reliability.
In practice, the decision comes down to usage pattern. Intermittent, experimental workloads lean toward Fireworks AI’s a‑la‑carte model, while continuous production pipelines with collaboration needs tilt toward Modal’s subscription tiers. Choose the vendor whose pricing language matches your operational rhythm, and you’ll avoid surprise bills.
Pricing verified on 2026-09-20.