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Groq vs Cerebras
Two custom-chip hosts chasing speed on open models. Cerebras is faster on GPT-OSS 120B; Groq is cheaper per token, steadier at the tail and carries a few more models.
By The Subconscious Team · Updated
Groq vs Cerebras: key differences
Groq and Cerebras are the two chip companies most developers compare for raw speed. Cerebras's wafer-scale chip lists GPT-OSS 120B near 3,000 tokens per second, about six times Groq's published 500 on the same weights. Groq answers with price and predictability. Its per-token rates on small models sit near the market floor, cache and Batch discounts stack, and its deterministic LPU schedule keeps median and tail latency close. Cerebras charges $0.35 in and $0.75 out on GPT-OSS 120B and, by its own account, costs more per token than Groq on shared models. Both catalogs are thin. Cerebras's shared list is GPT-OSS 120B and Gemma 4 31B; Groq's centers on GPT-OSS and Qwen 3.6.
Extras and outlook break the tie. Groq hosts Whisper for speech to text and Groq Compound, an agentic system with built-in search and code execution, which suits voice agents. Cerebras reaches more models through dedicated endpoints and partners like OpenRouter and AWS Marketplace, and it runs OpenAI's Ultrafast GPT-5.6 Sol preview. Groq's future is murkier since NVIDIA licensed the LPU and hired most of its engineers. Cerebras now trades publicly on Nasdaq.
What Groq and Cerebras do
Groq
Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq profileCerebras
Cerebras builds a single chip the size of a silicon wafer, and its inference cloud is the fastest public host on the models it serves. Its developer table lists GPT-OSS 120B near 3,000 tokens per second, about six times Groq on the same weights, at $0.35 in and $0.75 out per million. The public shared catalog is thin, just GPT-OSS 120B and Gemma 4 31B as of August 2026. More model families live on dedicated endpoints and through partners like OpenRouter, Hugging Face, Vercel and AWS Marketplace.
Example models: GPT-OSS 120B, Gemma 4 31B
Full Cerebras profileShould you choose Groq or Cerebras?
Groq
Choose Groq for
- Voice agents pairing Whisper with fast LLM replies
- Cost-sensitive small-model calls with stacked discounts
- SLAs judged on tail latency rather than peak speed
Cerebras
Choose Cerebras for
- Maximum tokens per second on GPT-OSS 120B
- Long streamed outputs in live code tools
- Access to GPT-5.6 Sol Ultrafast on wafer-scale hardware
Groq vs Cerebras at a glance
| Attribute | Groq | Cerebras |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | GPT-OSS 120B, Gemma 4 31B |
| Speed | 500–1,000 tok/s | ~3,000 tok/s on GPT-OSS 120B |
| Price | Near the floor on small models | $0.35 in, $0.75 out (GPT-OSS 120B) |
| Customization | No fine-tuned model hosting | Unknown |
| Deployment | GroqCloud API | Shared API, dedicated, partners |
| Long context | Around 131K max | Unknown |
Frequently asked questions
What is the difference between Groq and Cerebras?
Two custom-chip hosts chasing speed on open models. Cerebras is faster on GPT-OSS 120B; Groq is cheaper per token, steadier at the tail and carries a few more models.
When should I choose Groq over Cerebras?
Voice agents pairing Whisper with fast LLM replies; Cost-sensitive small-model calls with stacked discounts; SLAs judged on tail latency rather than peak speed.
When should I choose Cerebras over Groq?
Maximum tokens per second on GPT-OSS 120B; Long streamed outputs in live code tools; Access to GPT-5.6 Sol Ultrafast on wafer-scale hardware.
Is Groq or Cerebras cheaper?
Groq: Near the floor on small models. Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). The cheaper choice depends on the model and workload.
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