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Cerebras vs DeepInfra
Cerebras sells the fastest tokens on two shared models. DeepInfra sells the cheapest tokens across 150+. Speed-bound and cost-bound workloads split cleanly.
By The Subconscious Team · Updated
Cerebras vs DeepInfra: key differences
Cerebras and DeepInfra sit at opposite ends of the open-model market. Cerebras runs GPT-OSS 120B near 3,000 tokens per second on its wafer-scale chip, at $0.35 in and $0.75 out per million. DeepInfra competes on price instead, with Llama 3.1 8B at $0.02 per million and DeepSeek V4 Flash at $0.14 in and $0.28 out, no minimums or contracts. Catalog breadth is lopsided. The Cerebras shared API held two models as of August 2026, while DeepInfra carries 150+ across text, image and speech and adds new Hugging Face releases quickly.
DeepInfra's savings come partly from heavy quantization, which can cut quality and context length, as with its 66K cap on FP4 DeepSeek V4 Pro. Teams need to check precision per model. Cerebras' constraint is different: most models beyond its two shared ones mean a sales conversation. For voice, live autocomplete and long streamed outputs, Cerebras earns its price. For bulk extraction, tagging and synthetic data where nobody watches the tokens arrive, DeepInfra wins on cost.
What Cerebras and DeepInfra 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 profileDeepInfra
DeepInfra is the price floor for open-model inference. Developers treat it as the reference point for what a token should cost, with small models like Llama 3.1 8B at $0.02 per million and DeepSeek V4 Flash at $0.14 in and $0.28 out. The catalog covers 150+ open models across text, image and speech behind a fully OpenAI-compatible API. There are no minimums, setup fees or contracts on the shared API.
Example models: DeepSeek V4 Flash, Llama 3.1 8B
Full DeepInfra profileShould you choose Cerebras or DeepInfra?
Cerebras
Choose Cerebras for
- Voice and streaming UIs where generation time is the wait
- Long outputs on GPT-OSS 120B at about 3,000 tokens per second
- Dedicated endpoints for model families beyond the shared API
DeepInfra
Choose DeepInfra for
- Bulk extraction, tagging and synthetic data on a budget
- Picking from 150+ open models self-serve
- No-contract access to small models at $0.02 per million
Cerebras vs DeepInfra at a glance
| Attribute | Cerebras | DeepInfra |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Gemma 4 31B | DeepSeek V4 Flash, Llama 3.1 8B |
| Speed | ~3,000 tok/s on GPT-OSS 120B | ~33 tok/s on DeepSeek V4 Pro (FP4) |
| Price | $0.35 in, $0.75 out (GPT-OSS 120B) | From $0.02 per 1M |
| Customization | Unknown | No managed fine-tuning |
| Deployment | Shared API, dedicated, partners | Shared API, no contracts |
| Long context | Unknown | 66K on FP4 DeepSeek V4 Pro |
Frequently asked questions
What is the difference between Cerebras and DeepInfra?
Cerebras sells the fastest tokens on two shared models. DeepInfra sells the cheapest tokens across 150+. Speed-bound and cost-bound workloads split cleanly.
When should I choose Cerebras over DeepInfra?
Voice and streaming UIs where generation time is the wait; Long outputs on GPT-OSS 120B at about 3,000 tokens per second; Dedicated endpoints for model families beyond the shared API.
When should I choose DeepInfra over Cerebras?
Bulk extraction, tagging and synthetic data on a budget; Picking from 150+ open models self-serve; No-contract access to small models at $0.02 per million.
Is Cerebras or DeepInfra cheaper?
Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). DeepInfra: From $0.02 per 1M. 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.