Managed inference API
Cerebras Inference
Wafer-scale inference that owns the speed category alongside Groq — Llama-class 70B models at thousands of tokens per second on WSE-3 hardware.
Editorial scores last reviewed September 3, 2026
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Best for
Latency- and throughput-critical serving of supported Llama/Qwen-class models
Watch out
Curated model list narrower than general GPU clouds; premium per-token rates pay for the speed — verify your model is served before architecting around it. The rack-scale CS-4 (launched 2026-08-18, three WSE-3T wafers, up to 2x CS-3 speed and 10x token capacity) is rolling out alongside a 165MW Finland datacenter; GPT-5.6 Sol is served at up to 750 tokens/sec (2026-08-27)
| Billing | Per-token API pricing with free-tier trials |
|---|---|
| GPU choice | Cerebras WSE-3 wafer-scale hardware — no GPU SKU selection |
| Cold start | Typically warm API endpoints |
| Model access | Curated fast-serving set (Llama, Qwen, Mistral families) |
Fit detail
When Cerebras Inference is the right shortlist — and when it is not
Use these lists to kill bad comparisons early, before you compare logos.
Ideal for
- Agents and chat where tokens-per-second is the product
- High-throughput batch decode on supported models
- Speed benchmarks and demos
Usually not ideal for
- Models outside the curated catalog
- Custom fine-tunes or dedicated GPUs
- Price-first buying — speed is what you pay for
Spend & ops
How cost behaves — and what breaks first
No invented $/hour quotes. These notes explain the failure modes that show up on the first real invoice.
Cost mental model
Premium per-token rates bought with extreme tokens-per-second; pay-as-you-go with published model rates
Ops notes
- Throughput claims are per-model — measure your prompt shape
- Check rate-limit tiers before a launch spike
Fit scores
Cerebras Inference on the decision axes
Same editorial scale as the hub chart — useful for shortlists, not as a price quote.
- GPU choice1/10
- Time-to-serving (editorial)5/10
- Price clarity4/10
- Production ops3/10
- Open-model breadth2/10
Among all providers
GPU choice
Pick exact GPUs
Time-to-serving (editorial)
Warm-path fit
Price clarity
Easy to forecast
Production ops
Less DIY ops
Open-model breadth
Catalog depth
Scores are editorial planning ratings (1–10) for product shape — not published $/hour quotes or vendor SLAs. Verify current pricing on each provider site.
Related
Keep the decision attached to the rest of the stack
Cloud rental is one path. Local VRAM and open-weight fit still matter.