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Compare GPU and LLM inference API pricing between Cerebras and Runpod. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Cerebras Price | Runpod Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 PCIE 40GB VRAM • Runpod | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Runpod | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
A40 48GB VRAM • Runpod | Not Available | — | ||
A40 48GB VRAM • | ||||
B200 180GB VRAM • Runpod | Not Available | — | ||
B200 180GB VRAM • | ||||
H100 NVL 94GB VRAM • Runpod | Not Available | — | ||
H100 NVL 94GB VRAM • | ||||
H100 PCIe 80GB VRAM • Runpod | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Runpod | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Runpod | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • Runpod | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L4 24GB VRAM • Runpod | Not Available | — | ||
L4 24GB VRAM • | ||||
L40 40GB VRAM • Runpod | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • Runpod | Not Available | — | ||
L40S 48GB VRAM • | ||||
MI300X 192GB VRAM • Runpod | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 3070 8GB VRAM • Runpod | Not Available | — | ||
RTX 3070 8GB VRAM • | ||||
RTX 3080 10GB VRAM • Runpod | Not Available | — | ||
RTX 3080 10GB VRAM • | ||||
A100 PCIE 40GB VRAM • Runpod | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Runpod | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
A40 48GB VRAM • Runpod | Not Available | — | ||
A40 48GB VRAM • | ||||
B200 180GB VRAM • Runpod | Not Available | — | ||
B200 180GB VRAM • | ||||
H100 NVL 94GB VRAM • Runpod | Not Available | — | ||
H100 NVL 94GB VRAM • | ||||
H100 PCIe 80GB VRAM • Runpod | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Runpod | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Runpod | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • Runpod | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L4 24GB VRAM • Runpod | Not Available | — | ||
L4 24GB VRAM • | ||||
L40 40GB VRAM • Runpod | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • Runpod | Not Available | — | ||
L40S 48GB VRAM • | ||||
MI300X 192GB VRAM • Runpod | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 3070 8GB VRAM • Runpod | Not Available | — | ||
RTX 3070 8GB VRAM • | ||||
RTX 3080 10GB VRAM • Runpod | Not Available | — | ||
RTX 3080 10GB VRAM • | ||||
| Model ↑ | Cerebras | Runpod | Input Diff ↕ |
|---|---|---|---|
OpenAI | $0.350 in $0.750 out | Not available | — |
Kimi | Not available | $0.950 in $4.00 out | — |
Kimi | Not available | $0.950 in $4.00 out | — |
Moonshot | Not available | $3.00 in $15.00 out | — |
Alibaba | Not available | $10.00 in $10.00 out | — |
Alibaba | $0.990 in $1.49 out | Not available | — |
Explore how these providers compare to other popular GPU cloud services
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Compare Cerebras with another leading provider
Compare Cerebras with another leading provider
Compare Cerebras with another leading provider
Compare Cerebras with another leading provider
Compare Cerebras with another leading provider
Models run on the Cerebras Wafer-Scale Engine, which keeps model weights in on-chip SRAM to reach published speeds in the thousands of tokens per second
Chat Completions and Completions endpoints at api.cerebras.ai/v1, usable from the OpenAI SDKs or the Cerebras Python and TypeScript SDKs
Public endpoints serve unmodified open-weight models such as OpenAI GPT OSS and Qwen, with a documented policy of no pruning on hosted models
Configurable reasoning effort, streaming, structured outputs, parallel tool calling, and prompt caching across the catalog
Vision-capable models accept PNG and JPEG images alongside text
Private, provisioned endpoints on reserved capacity with fine-tuning, weight management, and additional model families, arranged through sales
Access to a wide range of GPU types with enterprise-grade security
Only pay for the compute time you actually use
Programmatically manage your GPU instances via REST API
Pods typically ready in 20-30 s
SSH & VS Code tunnels built-in
Automatic migration on pre-empt
On‑demand single‑node GPU instances in Secure Cloud (data‑center hosted) or lower‑cost Community Cloud, with flexible templates and storage.
Spin up multi‑node GPU clusters in minutes with auto networking.
Time-limited credits granted on signup, with lower rate limits and context windows than paid tiers
Prepaid credits billed per million input and output tokens at published per-model rates
Reserved capacity, higher rate limits, and additional models on custom terms through sales
Pods hosted in vetted data centers; higher reliability tier
Pods on vetted community hosts at lower rates — the on-demand prices shown here
Interruptible capacity at reduced prices
Sign up at cloud.cerebras.ai and add a payment method to activate the free trial
Generate a key from the Cloud Console
pip install cerebras_cloud_sdk or npm install @cerebras/cerebras_cloud_sdk, or use the OpenAI SDK pointed at api.cerebras.ai/v1
Call chat completions with a model ID from the catalog, such as gpt-oss-120b
Sign up for Runpod using your email or GitHub account
Add a credit card or cryptocurrency payment method
Select a template and GPU type to launch your first instance
Cerebras-operated data centers in North America, with expansion into Europe; no region selection on the public API
Documentation and API reference, model-specific guides, Cloud Console usage monitoring, Discord community, and enterprise support for dedicated customers