Target Performance Projected
TARGET LATENCY
<50ms
p50 at launch
TARGET THROUGHPUT
1M+ t/s
at full capacity
TARGET UPTIME
99.99%
SLA commitment
PLANNED REGIONS
14
at general availability
System Topology
How requests move through the platform
Edge Router
POST /v1/completions
routing: "geo-dns"
tls: "terminated"
rate_limit: "applied"
routing: "geo-dns"
tls: "terminated"
rate_limit: "applied"
Request Scheduler
queue: "priority"
model: "Kimi-K2.7"
region: "auto"
load: "balanced"
model: "Kimi-K2.7"
region: "auto"
load: "balanced"
Inference Engine
status: "streaming"
tokens: "284 emitted"
latency: "47ms p99"
cache: "hit"
tokens: "284 emitted"
latency: "47ms p99"
cache: "hit"
Capabilities
What the platform does
Elastic Scale
We handle the scaling. Traffic spikes are absorbed automatically. You never think about capacity.
Smart Routing
Geo-DNS with latency-based routing. Requests hit the nearest healthy region.
Token Streaming
First token in under 50ms. Stream responses token-by-token with sub-second TTFB.
Observability
Token-level logging, request tracing, cost attribution. Export to any stack.
Intelligent Cache
KV-cache reuse across requests. Automatic prompt deduplication.
Automatic Failover
Region failure detected in <1s. Traffic rerouted without dropping connections.
API Reference
Multiple models. One endpoint.
POST
/v1/chat/completions
// Multiple models. One endpoint.
{
"model": "GLM-5.2",
"messages": [{"role": "user", "content": "Hello"}],
"stream": true,
"temperature": 0.7
}
{
"model": "GLM-5.2",
"messages": [{"role": "user", "content": "Hello"}],
"stream": true,
"temperature": 0.7
}
200
/v1/chat/completions
// Streaming response
{
"id": "chatcmpl-...",
"model": "Kimi-K2.7",
"choices": [{
"delta": {"content": "Hello"}
}],
"usage": {"prompt_tokens": 12, "completion_tokens": 284}
}
{
"id": "chatcmpl-...",
"model": "Kimi-K2.7",
"choices": [{
"delta": {"content": "Hello"}
}],
"usage": {"prompt_tokens": 12, "completion_tokens": 284}
}
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