Serve your own LLMs at up to 3× the throughput.
SlipStream is a serving platform for the models you host yourself. It learns from live traffic and adapts its acceleration to each use case on its own, so the GPUs you already pay for do more work.
Up to 3× throughput compared with baseline serving, measured in internal benchmarks. Full test conditions will be published at launch.
Throughput across a simulated day
- Peak
- 2.4×
- Day average
- 1.8×
- Adaptations
- 18
More tokens from the same GPUs
Traffic changes by the hour. SlipStream learns each use case and keeps its acceleration matched to what your users send.
- Up to 3× throughput
- Compared with baseline serving, on the GPUs you already run. More tokens per GPU-hour means less compute to buy.
- Learns from live traffic
- The acceleration learns from the requests you actually serve and keeps adapting as traffic shifts through the day.
- Adapts per use case
- Support chat, retrieval and overnight batch jobs produce very different text. Each one gets acceleration adapted to its own traffic, updated automatically.
- Adapts within a response
- A single turn can move from reasoning to a tool call to a written answer. Each part gets its own acceleration as your model writes it.
- Three operating modes
- Pick what each use case should optimize: cost, latency, or a balance of both.
- Runs where your models run
- Our managed cloud, your own cloud account, or GPUs you own. Your models stay yours in all three.
How it adapts
The same loop runs for every use case, all day, independently.
Step 1
Learn
It watches each use case's live traffic: what the requests look like, what your model writes back, and how both change through the day.
Step 2
Adapt
When that traffic changes enough to matter, the use case's acceleration adapts automatically, aimed at the mode you picked.
Step 3
Serve
The adapted acceleration takes over on its own, with nobody hand-tuning anything. Your other use cases keep theirs.
Then back to step 1.
Tell it what matters
Choose a mode for each use case. Every adaptation aims at it.
| Mode | Optimizes for | Choose it for |
|---|---|---|
| Cost sensitive | The most tokens per GPU-hour | Batch jobs, internal tools, and workloads where cost per token decides. |
| Latency sensitive | The fastest responses | User-facing chat and agents, where every wait is visible. |
| Balanced | Cost and speed, weighed together | Mixed workloads, or when you haven't decided yet. |
Run it anywhere
Deploy it where your models live, on the stack you already run.
| Option | SlipStream runs | You control |
|---|---|---|
| SlipStream cloud | On infrastructure we manage | Your models and your endpoints |
| Your cloud (VPC) | Inside your own cloud account | The account, network and access policies |
| On-prem | On GPUs you own | The hardware and the network around it |
Get on the early-access list
We'll onboard a small group of teams before launch. Leave a work email and we'll be in touch when a slot opens.
Want to talk it through first? Contact the team