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Cerebras

by Cerebras Systems

AI inference chip and cloud service delivering 2000+ tokens/second LLM throughput — enabling APAC latency-critical applications where GPU inference speed is insufficient for real-time AI interaction, streaming, and rapid batch processing.

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AIMenta verdict
Niche use
3/5

"Ultra-fast LLM inference chip — APAC AI teams use Cerebras for sub-second LLM inference at 2000+ tokens/second, enabling APAC latency-critical applications where standard GPU inference is too slow for real-time APAC user experience."

Features
6
Use cases
1
Watch outs
3
What it does

Key features

  • Ultra-fast inference: 2,000-3,200 tokens/second vs APAC GPU 30-100 tokens/second
  • OpenAI-compatible: APAC API drop-in with base_url change
  • Llama 3.1 access: 8B and 70B at Cerebras wafer-scale speed
  • Streaming optimization: near-instant APAC token streaming for interactive applications
  • No hardware purchase: Cerebras cloud API for APAC pay-per-token access
  • Batch processing: rapid APAC bulk inference for classification and extraction jobs
When to reach for it

Best for

  • APAC AI teams with validated latency-critical requirements where GPU inference speed is insufficient — particularly APAC real-time transcription, interactive code generation, and live streaming applications where sub-second full-response generation materially improves user experience.
Don't get burned

Limitations to know

  • ! Premium pricing over GPU inference — APAC teams without strict speed requirements pay too much
  • ! Limited model choice — Cerebras cloud hosts specific APAC models, not all open LLMs
  • ! Niche use case — most APAC LLM applications work well with GPU inference latency
Context

About Cerebras

Cerebras is an AI hardware company providing wafer-scale chip technology and cloud inference service delivering 2,000-3,000+ tokens per second for LLM inference — 10-20x faster than GPU inference for the same LLM. APAC AI teams building latency-critical applications (real-time transcription, interactive code generation, live APAC content analysis) use Cerebras when GPU-based inference is too slow for their APAC user experience requirements.

Cerebras' Wafer Scale Engine (WSE) chip is the world's largest semiconductor — a single WSE provides the compute density of hundreds of GPUs without the interconnect overhead that limits GPU cluster LLM inference. For APAC applications needing rapid full-document generation (legal brief generation, APAC report writing, code generation for complete modules), Cerebras' throughput advantage reduces user wait time from tens of seconds to under a second.

Cerebras Inference API provides access to Llama 3.1 70B at 2,100 tokens/second and Llama 3.1 8B at 3,200 tokens/second — APAC teams can consume Cerebras' speed via an OpenAI-compatible API without purchasing hardware. For APAC streaming applications where users watch tokens appear, Cerebras' speed makes AI feel nearly instantaneous versus the 30-100 token/second typical of GPU inference.

Cerebras is positioned as a niche solution for APAC applications with explicit speed requirements — for most APAC LLM applications, GPU inference latency (1-3 second TTFT on GPU) is acceptable and Cerebras' premium pricing is not justified. APAC teams with documented latency requirements (user testing showing speed matters for their APAC use case) benefit most from Cerebras.

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