Cerebras vs Groq
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | Cerebras | Groq |
|---|---|---|
| Pricing | Freemium | Freemium |
| Speed | 1,800+ tok/s (Gemma 4 31B), 2,000+ tok/s (Meta Scout) | Sub-200ms latency |
| Key Architecture | Wafer-Scale Engine (58x larger than GPU) | Language Processing Unit (LPU) |
| Notable Models | Gemma 4, Meta Scout | GPT-OSS, Kimi K2 |
| Extra Capabilities | Model training, Multi-LoRA | Compound AI, Orpheus TTS, Batch API |
| Integrations | AWS, HuggingFace, Vercel, LiveKit | OpenAI SDK, BrowserBase, Stripe, Tavily |
If you need raw token throughput for heavy agentic workloads and want the ability to train as well as infer on the same platform, Cerebras is your pick. If you prioritize sub-200ms latency, flexibility with open-source models, and a rich ecosystem of agentic tools, go with Groq. Both are fast, but they target different pain points.
Cerebras delivers ultra-fast AI inference on wafer-scale hardware for latency-critical agents and apps.
Visit WebsiteGroq is an inference neocloud built for sub-200ms LPU inference — fast open-weight model serving for real-time chat, voice, and agent workloads.
Visit WebsiteWho should pick which
- Real-time code agent builderPick: Cerebras
Cerebras delivers over 2,000 tokens/sec on Meta Scout and 1,800+ on Gemma 4, enabling instant code generation without stalling—critical for agents that need sub-second responses.
- Voice AI developerPick: Groq
Groq's Orpheus TTS produces speech at 100+ chars/s with sub-200ms latency, making it ideal for real-time conversational voice applications.
- Enterprise with predictable cost needsPick: Groq
Groq offers linear, predictable pricing with batch discounts and prompt caching, way clearer than Cerebras's custom enterprise quotes.
- Multimodal AI researcherPick: Cerebras
Cerebras's support for multimodal models like Gemma 4 at high throughput, plus its training capabilities, suits research that needs both inference and fine-tuning.
- Agentic workflow orchestratorPick: Groq
Groq's Compound AI integrates web search, code execution, and browser automation in one call, plus Remote MCP, simplifying complex agent architectures.
Benchmarks
| Metric | Cerebras | Groq |
|---|---|---|
| Inference speed (tokens/second) | 2000+ tokens/secCerebras official claims | 1000 tokens/secGroq official claims |
| Latency (end-to-end) | <1 secondCerebras official claims | <0.1 secondGroq official claims |
| Speed improvement vs GPU | 15x timesCerebras official claims | 7.41x timesGroq official claims |
| Cost reduction vs GPU | N/A %Not claimed | 89 %Groq official claims |
Frequently Asked Questions
Cerebras vs Groq: which should you choose?
If you need raw token throughput for heavy agentic workloads and want the ability to train as well as infer on the same platform, Cerebras is your pick. If you prioritize sub-200ms latency, flexibility with open-source models, and a rich ecosystem of agentic tools, go with Groq. Both are fast, but they target different pain points.
Can I train models on Groq?
No, Groq focuses solely on inference; Cerebras supports both training and inference on the same platform.
Which platform has lower startup costs?
Groq is more transparent with freemium and linear pricing, while Cerebras may require custom enterprise agreements, making Groq easier to start with.
Does Cerebras support fine-tuning?
Yes, Cerebras offers Multi-LoRA for efficient fine-tuning, a feature not mentioned for Groq.
How do I integrate these APIs if I already use OpenAI?
Both are OpenAI-compatible; Groq switches in two lines of code, while Cerebras offers drop-in compatibility.
Which platform is better for global deployment?
Groq has global data centers for low-latency responses worldwide, while Cerebras is partnering internationally but less specified.
More Cerebras or Groq comparisons
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Last reviewed: August 3, 2026