# Fast-inference ASIC

**Source:** https://promtable.com/glossary/fast-inference-asic

> A fast-inference ASIC is a custom chip designed specifically for LLM token generation — Groq LPU, Cerebras CS-3/CS-4, SambaNova RDU, Tenstorrent are 2026 examples delivering 5-20× the tokens/s of GPUs at lower latency.

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A fast-inference ASIC is a custom chip designed specifically for LLM token generation — Groq LPU, Cerebras CS-3/CS-4, SambaNova RDU, Tenstorrent are 2026 examples delivering 5-20× the tokens/s of GPUs at lower latency.

GPUs were designed for graphics + general parallel compute; LLM inference exposes their inefficiencies (memory bandwidth bound on autoregressive decode). Fast-inference ASICs flip this: chip layout matches LLM access patterns — Groq LPU eliminates HBM with on-chip SRAM; Cerebras CS-3/CS-4 puts the entire model on a single wafer-scale chip; SambaNova RDU specializes in 'Composition of Experts'. Production benefits: 5-20× tokens/s, lower per-token cost on large open-weight models, ultra-low TTFT for voice agents. Trade-offs: smaller model menu than GPU clouds, vendor lock-in on hardware, less mature tooling. By 2026 fast-inference ASICs are mainstream for voice agents and high-throughput open-weight workloads; closed-weight frontier models (Claude, GPT) still run on GPUs.

## When to use

- Voice agents + real-time apps.
- High-throughput open-weight inference.

## Common mistakes

- Picking ASIC for closed-weight models — they're only available on GPU clouds.

## Related terms

- [lpu](https://promtable.com/glossary/lpu)
- [wafer-scale](https://promtable.com/glossary/wafer-scale)
- [throughput-per-dollar](https://promtable.com/glossary/throughput-per-dollar)

*Last updated: 2026-06-01*
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