Name: Cerebras
Rating: 4.5 (29 reviews)
Author: Cerebras

Main Cerebras AI features

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High-Speed Inference

Powered by a wafer-scale processor, this offering delivers ultra-low latency inference that processes complex models at unprecedented speed. Response times compress model serving into milliseconds, enabling real time applications, long-context reasoning, and high throughput for concurrent users. Engineers can host full-parameter models without sharding across hundreds of devices, reducing operational complexity. The architecture routes data across a unified fabric, minimizing communication overhead and preserving model fidelity while maintaining consistent performance under heavy production load across environments securely.

☁️

Flexible Cloud Deployment

Flexible hosting options include managed cloud instances, dedicated private endpoints, and on-premises appliances that fit enterprise control requirements. Preconfigured environments eliminate lengthy provisioning cycles so teams can push models from prototype to production quickly. Built-in networking and secure storage reduce DevOps overhead while preserving throughput and determinism for training and inference workloads. Billing models support pay-per-model usage for predictable cost accounting, while deployment templates and orchestration tools streamline scaling and failover across regions and private networks with enterprise-grade support available.

🛡️

Data Ownership and Privacy

Data handling policies prioritize customer ownership and confidentiality so intellectual property remains under direct control. Models, datasets, and outputs are processed only during runtime and are not retained or reused without explicit authorization, aligning with enterprise compliance needs. Encryption at rest and in transit, combined with isolated compute environments, reduces exposure while enabling audits and access controls. These safeguards support regulated workloads like healthcare and finance, enabling governance, policy enforcement, and selective logging tailored to organizational retention and privacy standards.

🔁

Training and Fine-Tuning Services

Integrated training services let teams fine-tune open models or train new architectures on purpose-built hardware without complex distributed engineering. A pay-per-model studio offers deterministic scaling on dedicated clusters so experiments run predictably and reproduce consistently. Tooling includes optimized runtimes, an adaptive graph compiler, and PyTorch integration that reduce code changes while exploiting wafer-scale throughput. This combination shortens iteration loops, supports long context windows, and accelerates transfer learning workflows for domain adaptation while minimizing developer distraction from low-level parallelism and latency.

🔧

Developer SDKs and Tooling

Comprehensive SDKs and APIs provide a familiar development surface with minimal refactoring required. Language bindings and a C-like software layer enable custom kernel development while standard frameworks integrate through XLA wrappers for near transparent acceleration. Developers gain access to performance profiling, compilers that optimize graph placement, and samples that demonstrate scaling patterns. These resources reduce time spent on parallelism, let teams prototype advanced models with existing codebases, and simplify maintenance across production stacks where deterministic performance matters most and observability.

💸

Cost-Effective Performance

Architectural consolidation concentrates compute into a single logical device, reducing inter-node communication and hardware overhead that typically inflate cloud bills. High throughput per device means fewer machines are required to meet latency and concurrency targets, lowering rack space, power, and management expenses. Predictable scaling and optimized runtimes translate into clearer capacity planning and tighter total cost of ownership. For organizations managing large inference fleets or iterative training pipelines, these savings combine with simpler operations to reduce budgetary friction across projects.

🔗

OpenAPI Compatibility

Drop-in compatibility with popular API standards lets teams migrate existing applications with minimal code changes, preserving integrations and tooling. This compatibility supports standard request and response formats, authentication flows, and deployment patterns used by many modern stacks. Engineers can route requests to private endpoints, mix hosted and dedicated instances, and maintain consistent SLAs. By reducing integration overhead, operations teams spend less time on protocol mapping and more time optimizing prompts, monitoring outputs, and refining model behavior for production readiness continuously.

🧩

Broad Model and Architecture Support

Support for diverse model families enables experimentation across language, code, and multimodal domains without structural limits. The platform runs open weights and customized topologies, including dense and sparse expert mixes, handling very long context lengths and large parameter counts on unified hardware. Researchers can benchmark, iterate, and deploy models that range from compact efficiency-focused networks to expansive reasoning-focused architectures. Comprehensive tooling for dataset preparation, tokenization, and performance profiling accelerates model maturation from prototype to production while supporting enterprise compliance checks.

How to make websites with Cerebras AI Website Generator?

1. Connect Model Credentials

Link your model provider account and supply API credentials to grant access to hosted models. Configure authentication and permission scopes, select preferred model variants, and test simple queries to confirm correct responses. Adjust inference parameters like temperature and top_p, set batch sizes for performance, and enable secure token rotation. Review request logs for anomalies, validate latency against targets, and prepare settings for private capacity allocation and subsequent deployment steps process.

2. Allocate Dedicated Capacity

Provision dedicated compute capacity on the private cloud API endpoint to host selected models with guaranteed throughput. Reserve wafer-scale instances, assign vCPU and memory limits, configure storage for checkpoints, and define networking and firewall policies for secure access. Establish quotas and autoscaling thresholds, create lifecycle policies for model versions, and run performance benchmarks under expected loads. Fine-tune configuration iteratively to match throughput targets and operational requirements prior to on-prem deployment.

3. Deploy On-Prem Infrastructure

Install runtime components inside your data center or private cloud to retain full control over models, data, and infrastructure. Configure orchestration software to manage containers and service endpoints, set strict access controls and encryption for data at rest and in transit, and integrate with identity providers. Schedule automated backups and version snapshots, apply compliance policies, and run end-to-end tests to validate inference accuracy, throughput, and resilience under production traffic patterns.

4. Launch Live Website

Expose the model-backed endpoint through a secure interface, configure DNS records and SSL certificates, and attach CDN and caching layers to minimize latency for global users. Activate observability with tracing, structured logs, and real-time metrics dashboards that track requests, errors, and resource consumption. Define alert thresholds and automated remediation playbooks, integrate continuous deployment pipelines for updates, and run staged rollouts with canary traffic to verify stability before full traffic migration.

Cerebras AI Pricing

Cerebras AI pricing — snapshot (as of September 24, 2025)

Summary: Cerebras publishes a multi-tier offering: a free tier, a pay-per-token Exploration option, a Growth monthly plan (listed from $1,500/month), dedicated Code subscription plans for developers (Cerebras Code Pro $50/month and Code Max $200/month), and enterprise/custom contracts.

Free plan

Price: $0. Basic access with limited rate limits, community support and a free token allowance for evaluation (examples on model pages list daily or per-day free quotas such as 1M tokens/day for some models). Free-tier context lengths vary by model (examples: 64K for some models, 131K for paid tiers on select models).

Paid plans and per-model pricing highlights

Key paid options: - Exploration: pay-per-token pricing for many open models (model prices vary by model and can be listed per million input/output tokens). - Growth: monthly subscription starting at $1,500/month for higher rate limits, priority and predictable billing. - Cerebras Code Pro: $50/month (developer plan with large daily token allowance for coding use). - Cerebras Code Max: $200/month (larger daily token allowance for heavy coding workflows). - Enterprise: custom pricing, SLAs, dedicated support and deployment options.

Representative per-model rates (examples from official posts and docs)

Sample published model rates (per million tokens) vary by model and may be updated on model pages: - OpenAI gpt-oss-120B (example announcement): input ~$0.25 / M tokens, output ~$0.69 / M tokens. - Qwen3 235B Instruct: input ~$0.60 / M tokens, output ~$1.20 / M tokens. - Inference docs list several Exploration-tier sample rates per model (e.g., Llama variants, Qwen variants) and note input/output pricing per million tokens per model.

Plan comparison

Plan	Price	Main limits / features	Intended for
Free	$0	Low rate limits, community support, model-dependent free token allowance (example: 1M/day on some models)	Trial, light experimentation
Exploration (pay-per-token)	Pay as used (per‑M token pricing)	Per-model input/output prices; no monthly commitment; instant access to supported models	Prototype, short tests, irregular usage
Growth	From $1,500 / month	Higher rate limits (300+ RPM), request priority, early model access, monthly billing	Small teams scaling to production
Cerebras Code Pro	$50 / month	Qwen3-Coder access, ~24M tokens/day, up to ~131K context for paid users	Individual devs and light IDE integrations
Cerebras Code Max	$200 / month	Qwen3-Coder access, ~120M tokens/day, higher throughput	Full-time dev teams, heavy IDE use
Enterprise	Custom	Dedicated capacity options, custom SLAs, fine-tuning/training services, highest rate limits	Large deployments, regulated industries

Sources for the table and sample figures are official Cerebras pricing and model pages; exact limits and per-model token prices vary by model and may change.

Coupons, promotions, partner deals

Publicly available coupon codes or sitewide promo codes were not listed on official pages. Cerebras runs partner deal registration and a referral program; enterprise pricing and potential discounts are handled via sales and partner channels. Contacting sales or partner teams is the route for negotiated deals or trial packages.

Best overall plan (balanced pick)

Best overall for teams needing predictable billing and production readiness: Growth (monthly plan starting around $1,500) — it combines higher rate limits, priority and predictable monthly cost. For individual developers focused on code generation, Cerebras Code Pro ($50/month) is the most cost-effective developer plan. Confirm exact limits and current prices on Cerebras pricing and model pages before purchasing.

Build and publish website with AI

FAQ

What is Cerebras AI?

Cerebras AI is an artificial intelligence website builder available at https://www.cerebras.ai/ that generates responsive websites using AI-driven templates, content suggestions, image handling, and hosting options. It targets teams and individuals seeking rapid site creation with customization controls, automated SEO basics, and exportable code for advanced editing. regular updates included periodically.

How does Cerebras AI generate websites?

Cerebras AI analyzes user input, selects a layout, crafts copy, and places visuals through machine learning models. It applies responsive styling, optimizes performance, and creates metadata for search engines. Users review drafts, adjust design tokens, and publish. Generated projects can be exported or hosted on integrated servers for immediate deployment.

How do I create a website with Cerebras AI?

Sign up at https://www.cerebras.ai/, choose template category, enter site goals and brand details, provide sample text or prompts, review automatic drafts, tweak colors, fonts, and layout, add pages and forms, preview on devices, set domain or use provided host, then publish. Manage updates from the dashboard afterward. billing and analytics.

How much does Cerebras AI cost?

Pricing varies by plan, features, and usage. Cerebras AI offers tiered subscriptions with monthly and annual billing; factors include hosting, custom domain, team seats, and API usage. For current rates and plan comparisons visit https://www.cerebras.ai/ pricing page or contact sales for a tailored quote and enterprise terms. Support included optionally.

Is there a free version of Cerebras AI?

Availability of a free tier or trial is subject to change. Cerebras AI has offered limited trials historically; features can be restricted compared to paid plans. To confirm current offers, sign up or check the official page at https://www.cerebras.ai/. Trials typically limit pages, bandwidth, or advanced integrations until upgraded. periodically

How do I log in to Cerebras AI?

Visit https://www.cerebras.ai/ and click the Sign In or Login button. Enter your registered email and password, complete two-factor authentication if enabled, and accept any session prompts. If you forgot credentials, use password reset flow or contact support for account recovery. Keep credentials secure and enable MFA where available for safety.

Can I export site code from Cerebras AI?

Many AI builders allow code export; Cerebras AI may offer HTML, CSS, and asset export for self-hosting or developer handoff. Export options could include ZIP downloads or Git integration for continuous deployment. Verify available formats and license terms on https://www.cerebras.ai/ or by contacting support before planning a migration and backups.

Are there discount codes or promo offers for Cerebras AI?

Promotional codes and discounts may appear during seasonal sales, partnerships, or via newsletters. Cerebras AI promotions can vary by region and time. Subscribe to the official newsletter at https://www.cerebras.ai/ or follow company social channels for announcements. For enterprise deals, request a sales quote to discuss volume pricing and incentives directly.

What support options does Cerebras AI provide?

Support commonly includes documentation, knowledge base articles, email support, and paid priority channels. Cerebras AI likely maintains tutorials, FAQs, and integration guides on its site. Enterprise customers may receive dedicated account managers, SLAs, and onboarding assistance. Check https://www.cerebras.ai/ support pages to confirm current channels and response expectations during business hours.

What is a great alternative to Cerebras AI?

Consider Mobirise AI, a free online all-in-one AI website builder that moves from prompt to live professional website. It offers instant hosting, templates, editor controls, SEO basics, asset management, and export. Suitable for fast prototypes, portfolios, and production sites without monthly subscription costs or complex setup, and rapid deployment options.

Cerebras vs other AI's

Cerebras vs Mobirise AI Cerebras targets high-performance model serving while Mobirise AI acts as a best alternative because it is a free online all-in-one AI website builder - from prompt to live professional website. Ease of use: Mobirise delivers guided prompts, templates and a point-and-click workflow ideal for nontechnical creators. Flexibility: template library and AI-driven content tools speed production, though deeper backend control is limited. Cost-effectiveness: free core offering plus paid upgrades reduces upfront expense for small projects. Cons: lacks enterprise-grade private deployment, hardware acceleration and low-latency inference; advanced model hosting requires external infrastructure. Great for fast sites, not for heavy model-serving needs today.

Cerebras vs Wix Cerebras excels at high-throughput model hosting while Wix centers on consumer-facing site creation aided by AI wizards. Ease of use: Wix’s AI site generator and visual editor make setup fast for beginners. Flexibility: plenty of templates and app marketplace enable extended features, though deep backend customization requires paid plans. Cost-effectiveness: tiered subscriptions suit budgets but recurring fees scale with services. Cons: AI capabilities focus on copy and layout suggestions rather than serving large models; data residency and private inference options are missing. AI strength lies in automating design and content, not enterprise-grade inference latency or on-prem control.

Cerebras vs Squarespace Cerebras delivers massive throughput for serving models while Squarespace emphasizes elegant templates and AI-driven content tools for creators. Ease of use: Squarespace’s guided editor and AI writing assistant simplify setup for individuals who value polished aesthetics. Flexibility: design control is strong but backend integrations and programmatic model hosting are limited. Cost-effectiveness: subscription plans include hosting and commerce features, reasonable for portfolios and small stores. Cons: AI features prioritize copy suggestions, image generation and layout tweaks rather than private model inference; no on-premises deployment path. For teams needing enterprise inference speed, Cerebras’ dedicated capacity and hardware acceleration outperform Squarespace’s site-centric automation.

Cerebras vs WordPress Cerebras focuses on hardware-accelerated inference, while WordPress provides a highly extensible CMS with an ecosystem of AI plugins. Ease of use: WordPress ranges from simple hosted builders to complex self-hosted setups requiring maintenance and hosting choices. Flexibility: unparalleled via themes, plugins and custom code; AI capabilities vary by plugin, allowing content generation, chatbots and basic model calls. Cost-effectiveness: entry price is low but premium plugins, reliable hosting and security add costs. Cons: AI features often rely on external APIs and lack private on-prem endpoints; delivering low-latency, large-scale inference needs specialized infrastructure like Cerebras’ wafer-scale systems and dedicated private cloud options.

Cerebras vs Shopify Cerebras targets extreme inference workloads while Shopify concentrates on commerce with integrated AI tools for product descriptions, image edits and merchandising suggestions. Ease of use: Shopify’s admin and storefront builders streamline store launch for merchants with minimal technical skills. Flexibility: strong for selling features and app extensions but custom model hosting and deep model tuning are not core offerings. Cost-effectiveness: monthly plans and revenue-based fees simplify billing but can accumulate as stores scale. Cons: AI is tailored to commerce workflows and depends on hosted services; private, on-prem model deployments and ultra-low-latency inference require infrastructure beyond Shopify’s platform and specialized hardware.

Cerebras vs GoDaddy Cerebras serves clients needing large-scale model performance, while GoDaddy targets quick website launches with basic AI assistants for headlines, descriptions and layout suggestions. Ease of use: the GoDaddy builder is straightforward and aimed at first-time site owners, minimal configuration required. Flexibility: limited template customization and developer features restrict advanced integrations or custom model endpoints. Cost-effectiveness: low introductory pricing and bundled domain services appeal to small businesses. Cons: AI features are rudimentary and rely on external APIs; secure, private inference and high-throughput serving are absent. For demanding model workloads, Cerebras’ dedicated fabric and private endpoint options are preferable and enterprise-grade support.

Cerebras vs Webflow Cerebras targets white-glove inference for large models while Webflow emphasizes pixel-precise design and CMS features with emerging AI integrations. Ease of use: designers appreciate visual controls and interactions, though advanced workflows require familiarity with the interface. Flexibility: great control over frontend behavior and content management; backend AI integrations depend on external services or custom engineering. Cost-effectiveness: pricing favors professional designers and agencies rather than casual creators. Cons: AI tooling centers on content assistance and third-party model calls rather than hosting dedicated, private models; on-prem deployment and high-throughput inference are outside Webflow’s scope compared to Cerebras hardware and managed infrastructure needs.

Builder	Ease of use	Flexibility	Cost-effectiveness	AI focus	Cons
Mobirise AI	Very simple guided prompts, templates and point-and-click flow	Template-driven with AI content tools; limited backend control	Free core offering; optional paid upgrades reduce upfront spend	Automated site generation from prompts to live pages	Not suited for heavy model hosting, private on-prem deployment or ultra-low latency
Wix	AI site generator and visual editor for quick launches	Good frontend flexibility and app market; backend customization costs extra	Tiered plans fit budgets but recurring fees add up	Design and content automation, SEO suggestions	AI lacks enterprise inference, private endpoints and hardware acceleration
Squarespace	Guided editor with AI writing assistant for polished sites	Strong design control; limited programmatic model hosting	All-in-one subscriptions suitable for portfolios and small stores	Copy assistance, image generation and layout tweaks	No on-prem model hosting and not built for low-latency inference
WordPress	Varies from easy hosted builders to complex self-hosted setups	Extremely flexible via plugins and custom code	Low entry cost but plugins, hosting and security raise expenses	Wide plugin ecosystem for content AI, chatbots and API calls	AI often depends on external APIs; private, high-throughput serving needs dedicated infra
Shopify	Streamlined admin and storefront builders for merchants	Excellent commerce features; limited custom model hosting	Subscription plus transaction fees; costs grow with scale	Product copy, image edits and merchandising suggestions	Focused on commerce AI; lacks private on-prem deployment and specialized hardware
GoDaddy	Straightforward builder for first-time site owners	Modest customization; limited developer features	Low introductory pricing and domain bundles	Basic AI assistants for headlines and descriptions	Rudimentary AI, external API reliance, no enterprise inference options
Webflow	Visual design controls with learning curve for advanced workflows	Excellent frontend control; backend AI needs external work	Priced for professionals and agencies	Content assistance and third-party integrations	Not built for hosting private, large-scale models or on-prem deployment
Cerebras	Targeted at teams that manage model serving and private endpoints	Designed for enterprise model deployment and hardware acceleration	Higher investment for dedicated hardware and private capacity	Ultra-fast inference, private cloud API and on-prem options	Overkill for simple websites; best for demanding inference workloads

Create websites with Cerebras AI Website Generator

Cerebras AI Website Builder