The inference API for latency-critical workloads
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The inference API for latency-critical workloads
A single slow request breaks a voice turn, misses a trade window, or triggers user abandonment.
Alloy runs on custom FPGA inference cards. Memory bandwidth, kernel scheduling, and attention computation are optimized end-to-end for transformer workloads — no GPU contention, no competing tenants, no driver overhead. A direct path from request to token, predictable by design.
Conversational AI that hesitates doesn't get a second chance. When TTFT drifts above 150ms, users detect the lag, call abandonment rises, session depth drops. Alloy holds P99 TTFT under 180ms across concurrent load, keeping voice flows natural at any scale.
Product questions during a livestream have a zero-second tolerance window. Viewers who don't get instant answers scroll past. Alloy powers real-time product lookup, recommendation, and Q&A on streams handling millions of concurrent viewers.
Completions that arrive after the developer has already moved on aren't completions. They're interruptions.. Staying under 200ms keeps suggestions invisible and actually used. Alloy keeps large-context completions fast enough to feel native.
Threat scoring is only actionable in the moment. Models that can't keep pace with event ingestion create false confidence — not real coverage. Alloy processes security events at the speed they arrive, with no queue buildup under load.
| Model | Speed | Latency | Status |
|---|---|---|---|
Llama 3 8B
Live
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1,000–3,000 T/s | <200ms | ● Available |
DeepSeek
Coming Soon
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— | — | ○ Waitlist |
Qwen
Coming Soon
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— | — | ○ Waitlist |
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Bring Your Own Model
Deploy any open-weight model on Alloy FPGA infrastructure
Request deployment →
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Alloy is OpenAI API-compatible. If you're already on Groq, OpenAI, or any other provider, swap two environment variables and you're live. No SDK changes. No migration work. Same interface, better guarantees.
# Change these two lines from your existing Groq / OpenAI setup import os import openai client = openai.OpenAI( base_url="https://api.alloycompute.com/v1", api_key=os.environ.get("ALLOY_API_KEY") ) response = client.chat.completions.create( model="llama-4-maverick", messages=[{"role": "user", "content": "Hello"}] )
// Change these two lines from your existing Groq / OpenAI setup import OpenAI from "openai"; const client = new OpenAI({ baseURL: "https://api.alloycompute.com/v1", apiKey: process.env.ALLOY_API_KEY, }); const response = await client.chat.completions.create({ model: "llama-4-maverick", messages: [{ role: "user", content: "Hello" }], });