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Cerebras vs Novita AI
Novita offers 200+ cheap models across text and media. Cerebras offers two shared models at the fastest published speeds of any public host.
By The Subconscious Team · Updated
Cerebras vs Novita AI: key differences
Novita AI is built for breadth and price. Its serverless API covers 200+ open models across LLMs, image, video, speech, voice cloning and embeddings, from $0.02 per million tokens, with batch at 50% off and a GPU cloud and agent sandbox on the same account. Cerebras is built for speed, running GPT-OSS 120B near 3,000 tokens per second at $0.35 in and $0.75 out, with Gemma 4 31B the only other shared model as of August 2026. Novita gets new open models on day zero, while Cerebras routes most models to dedicated endpoints and a sales conversation.
Enterprise buyers will find trade-offs on both sides. Novita has no public SOC 2, HIPAA or VPC peering, and runs looser serverless SLAs with Discord-based support. Cerebras is a Nasdaq-listed company with OpenAI as an anchor customer and distribution through AWS Marketplace. Cost-first indie products and prototypes fit Novita. Voice agents and streaming UIs that need the fastest tokens fit Cerebras.
What Cerebras and Novita AI do
Cerebras
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 profileNovita AI
Novita AI is a San Francisco inference cloud founded in late 2023 by Frank Lewis and Junyu Huang, and it competes on price and breadth. Its serverless API covers 200+ open models across LLMs, image, video, speech, voice cloning and embeddings, with LLM prices starting at $0.02 per million tokens. The API speaks both OpenAI and Anthropic formats. It became an official Hugging Face Inference Partner in April 2026 and was the day-zero launch partner for Google's Gemma 4.
Example models: DeepSeek V4 Pro, Gemma 4
Full Novita AI profileShould you choose Cerebras or Novita AI?
Cerebras
Choose Cerebras for
- The fastest output for voice and streaming UIs
- GPT-OSS 120B at about 3,000 tokens per second
- Procurement through AWS Marketplace
Novita AI
Choose Novita AI for
- Cost-first text and image generation for indie apps
- A wide multimodal catalog with day-zero model support
- Model APIs, GPUs and sandboxes on one bill
Cerebras vs Novita AI at a glance
| Attribute | Cerebras | Novita AI |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Gemma 4 31B | DeepSeek V4 Pro, Gemma 4 |
| Speed | ~3,000 tok/s on GPT-OSS 120B | ~36 tok/s on DeepSeek V4 Pro |
| Price | $0.35 in, $0.75 out (GPT-OSS 120B) | From $0.02 per 1M; batch 50% off |
| Customization | Unknown | Hot-swappable LoRA adapters |
| Deployment | Shared API, dedicated, partners | Serverless, GPU cloud, dedicated |
| Long context | Unknown | Full 1M on DeepSeek V4 Pro |
Frequently asked questions
What is the difference between Cerebras and Novita AI?
Novita offers 200+ cheap models across text and media. Cerebras offers two shared models at the fastest published speeds of any public host.
When should I choose Cerebras over Novita AI?
The fastest output for voice and streaming UIs; GPT-OSS 120B at about 3,000 tokens per second; Procurement through AWS Marketplace.
When should I choose Novita AI over Cerebras?
Cost-first text and image generation for indie apps; A wide multimodal catalog with day-zero model support; Model APIs, GPUs and sandboxes on one bill.
Is Cerebras or Novita AI cheaper?
Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). Novita AI: From $0.02 per 1M; batch 50% off. The cheaper choice depends on the model and workload.
Related comparisons
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If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.