Cerebras Cloud
Verified ProviderWafer-Scale Hardware Cloud 4.9 / 5.0 (92 reviews)World's Fastest AI Inference Engine (Wafer-Scale Engine CS-3)
Cerebras Cloud delivers unprecedented open LLM inference speeds powered by the CS-3 Wafer-Scale Engine. With 44GB of on-chip SRAM eliminating traditional memory bandwidth bottlenecks, Cerebras achieves 1,800 to 2,100 tokens/sec on Llama 3.3 70B, making it the premier choice for real-time voice agents, sub-100ms TTFT requirements, and multi-turn agentic reasoning loops.
Cerebras Cloud Serverless AI Token Inference Pricing (4 Models)
| AI Model | Category | Cold Start | Context Window | Input ($/1M or Unit) | Output / 1M Tokens | Speed | Actions |
|---|---|---|---|---|---|---|---|
| Llama-3.1-8B-Instant | LLM | 0s Instant | 128K tokens | $0.10 | $0.10 | 2150 tps | |
| Llama-3.3-70B-Instruct | LLM | 0s Instant | 128K tokens | $0.60 | $0.60 | 1850 tps | |
| Qwen-2.5-72B-Instruct | LLM | 0s Instant | 128K tokens | $0.60 | $0.60 | 1750 tps | |
| DeepSeek-R1-Distill-Llama-70B | REASONING | 0s Instant | 128K tokens | $0.65 | $0.65 | 1800 tps |
Cerebras Cloud Monthly API Token Spend Simulator
Simulate monthly inference cost across open foundation models. Zero idle cluster fees, pure pay-per-token API billing.
Unlike renting raw GPU instances where stopped persistent volumes incur $0.10/GB/month and idle compute bills 24/7, Cerebras Cloud charges purely for generated tokens. When your app receives zero traffic, your hourly cost is strictly $0.00.
Total volume: 25.0M tokens / month
Equivalent volume on OpenAI GPT-4o costs approx. $100/mo ($2.50/$10.00 per 1M).
- •Not a GPU: powered by Wafer-Scale Engines (WSE-3). Strict focus on LLM token inference and model pre-training; no arbitrary CUDA/C++ kernels.
- •Only accessible via OpenAI-compatible REST API endpoints and enterprise cluster agreements.
- •Fixed context window and model selection (Llama 3.3, Llama 3.1, DeepSeek R1 Distill, Qwen 2.5).
- ✓Fastest token output speed in the entire AI industry: generates ~1,800 to 2,100 tokens/second on Llama-3.1-8B and ~450 t/s on 70B.
- ✓Drop-in replacement for OpenAI API: set `base_url='https://api.cerebras.ai/v1'` and `api_key` for immediate 10x-20x streaming speedups.
- ✓Ideal for real-time agentic reasoning, code evaluation loops, and interactive chat where latency is user-critical.
Top Alternatives to Cerebras Cloud
Evaluate competing serverless inference APIs for pricing, speed, and platform reliability.
LPU inference engine with mature ecosystem and broader model choices
Groq offers widely deployed infrastructure with proven stability, lower per-token pricing on lightweight models, and high developer adoption.
Lowest cost per million tokens for background workloads
If your workload does not require 1,800+ tokens/sec, DeepInfra cuts your token bill in half with standard OpenAI-compatible endpoints.
In-Depth Technical Head-to-Head Battles:
Cerebras achieves unprecedented raw velocity on Llama 3.3 70B (1,850 tokens/sec vs Groq's ~310 tokens/sec) thanks to its massive 44GB on-chip SRAM Wafer-Scale Engine. Groq holds advantages in wider public awareness, proven SDK tooling, and lower token costs on lightweight 8B models. For real-time voice agents and multi-step agent reasoning, Cerebras is currently unmatched.
SambaNova and Cerebras represent the pinnacle of specialized non-GPU AI accelerators. SambaNova SN40L RDUs dominate for ultra-large models, delivering the world's fastest full-precision Llama 3.1 405B inference at 105+ tps. Cerebras CS-3 holds the absolute world record for 70B and 8B models, delivering an astonishing 2,100+ tokens/second via 44GB of wafer-integrated SRAM.
Developer API SDK & Code Recipes for Cerebras Cloud
Tested OpenAI-standard drop-in code snippets for Python, TypeScript, and cURL.
# 1. Install official OpenAI client:
# pip install openai
from openai import OpenAI
import os
client = OpenAI(
base_url="https://api.cerebras.ai/v1",
api_key=os.environ.get("CEREBRAS_API_KEY", "your_api_key_here")
)
response = client.chat.completions.create(
model="llama-3.3-70b",
messages=[
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "Explain KV cache compression in 3 concise bullet points."}
],
temperature=0.6,
)
print(response.choices[0].message.content)Cerebras Cloud Architecture, Gotchas & Engineering Verdict
Cerebras Cloud operates high-throughput managed inference clusters optimized for ultra-low latency token generation. Physical accelerators (LPUs or H100s) are pooled into an elastic API backend with zero user DevOps management.
- ✓Zero idle server cost: strictly pay-per-token with $0.00 disk retention fees.
- ✓OpenAI-compatible drop-in endpoints with streaming SSE and tool calling.
- ✓Instant autoscaling from 1 to 500+ concurrent requests with zero cold starts.
- !Rate Limits (TPM/RPM): Unverified free tiers have tighter request-per-minute limits. Upgrade to production tier for high concurrency.
- !Context Window Limits: Ensure long document RAG pipelines respect model context limits.
- !Fixed Model Catalog: You cannot run arbitrary custom LoRA checkpoints directly without dedicated custom endpoints.
Developer Reviews & Telemetry Audit
Aggregated from 92 verified AI engineers deploying vLLM, ComfyUI, and production API workloads.
“We migrated our full duplex voice pipeline to Cerebras. Sub-100ms TTFT and near-instant completion means our voice agents now respond faster than a human conversation.”
“When an agent executes 15 internal reasoning steps, standard GPU token speeds cause 45-second user wait times. On Cerebras CS-3, the entire 15-step loop finishes in 3.8 seconds.”