# Cerebras vs Inference.net

> Inference.net runs batch on spare GPU capacity with day-scale windows. Cerebras runs real-time generation at about 3,000 tokens per second.

Canonical: https://www.subconscious.dev/compare/cerebras-vs-inference-net · By The Subconscious Team · Updated September 30, 2026

## How they compare

Time is the dividing line. Inference.net started by buying idle GPU time and still reflects it: its Batch API takes up to 1M requests per file with completion windows from 24 hours to 7 days, priced off discounted spare capacity. Cerebras sells the opposite, serving GPT-OSS 120B near 3,000 tokens per second on a wafer-scale chip. Inference.net's own profile says fragmented spare capacity suits batch better than strict real-time SLAs, and real-time generation is exactly what Cerebras does best. The two rarely compete for the same request.

Inference.net also sells a loop from traffic to custom model: route requests through its gateway, capture them, turn them into training data, and deploy a distilled task-specific model on a dedicated GPU with a 99.99% uptime target. Cerebras' strengths are speed and an unusual link to closed models through OpenAI's Ultrafast preview. Each has limits on proof or breadth. Inference.net has few independent benchmarks, and the Cerebras shared catalog is only two models. Offline extraction and synthetic data belong on Inference.net. Voice and streaming belong on Cerebras.

## What each one does

### 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.

### Inference.net

Inference.net started as a buyer of last resort for idle GPU time. Its scheduler aggregates small unused chunks of capacity across data centers and runs models on them, and it passes the steep discounts it gets from those data centers on to customers. That origin still shows in its OpenAI-compatible Batch API, which takes up to 1M requests per file with completion windows from 24 hours to 7 days and far higher headroom than synchronous limits.

## Which is best, and when

### Choose Cerebras for

- Real-time voice and streaming generation
- Strict latency needs on GPT-OSS 120B
- Long outputs a user watches arrive

### Choose Inference.net for

- Million-request offline jobs with 24-hour to 7-day windows
- Distilling a narrow workload into a custom model
- One gateway key over open, closed and custom models

## At a glance

| Attribute | Cerebras | Inference.net |
|---|---|---|
| Model access | Open weights | Open, closed and custom |
| Flagship models | GPT-OSS 120B, Gemma 4 31B | Customer fine-tunes |
| Speed | ~3,000 tok/s on GPT-OSS 120B | Batch windows of 24h to 7 days |
| Price | $0.35 in, $0.75 out (GPT-OSS 120B) | Discounted spare GPU capacity |
| Customization | - | Distill traces into custom models |
| Deployment | Shared API, dedicated, partners | Batch API, gateway, dedicated GPUs |
| Long context | - | Varies by model |

## FAQ

### What is the difference between Cerebras and Inference.net?

Inference.net runs batch on spare GPU capacity with day-scale windows. Cerebras runs real-time generation at about 3,000 tokens per second.

### When should I choose Cerebras over Inference.net?

Real-time voice and streaming generation; Strict latency needs on GPT-OSS 120B; Long outputs a user watches arrive.

### When should I choose Inference.net over Cerebras?

Million-request offline jobs with 24-hour to 7-day windows; Distilling a narrow workload into a custom model; One gateway key over open, closed and custom models.

### Is Cerebras or Inference.net cheaper?

Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). Inference.net: Discounted spare GPU capacity. The cheaper choice depends on the model and workload.

## Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs Cerebras](https://www.subconscious.dev/compare/subconscious-vs-cerebras.md), [Subconscious vs Inference.net](https://www.subconscious.dev/compare/subconscious-vs-inference-net.md).

Full profiles: [Cerebras](https://www.subconscious.dev/providers/cerebras.md), [Inference.net](https://www.subconscious.dev/providers/inference-net.md).