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Anthropic vs Cerebras: Token Pricing, Speed & Intelligence

Full comparison of Anthropic and Cerebras — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.

Anthropic

Claude — safety-focused frontier AI with exceptional coding ability

Anthropic builds the Claude model family, known for long context windows (up to 200K tokens), strong coding performance, and a safety-first design philosophy. Claude 4 Opus and Sonnet lead on many coding and reasoning benchmarks. Prompt caching is available at significant discounts.

CodingReasoningLong-contextChatAgents
Proprietary models

Cerebras

Wafer-scale AI chips — 4,500 tokens/sec, the fastest inference on earth

Cerebras uses wafer-scale silicon (the CS-3 chip covers an entire silicon wafer) to deliver extraordinary inference throughput. Llama 3.1 8B runs at 4,500+ tokens/second — roughly 10× faster than GPU-based providers. This makes Cerebras uniquely suited for real-time applications, voice AI, and interactive coding assistants.

Voice AIReal-time chatSpeedInteractive codingStreaming
Open-weight hostHosts open weights

Key metrics

Cheapest input ($/1M)

Cheapest output ($/1M)

Peak throughput

Best latency (TTFT)

Intelligence score

Context window

Live token pricing

Strengths & weaknesses

Anthropic

Top coding benchmark scores (Claude 4 Opus)
200K context window on all Claude models
Aggressive prompt caching — up to 90% discount
Strong instruction-following and safety alignment
Extended thinking / reasoning mode on Opus
No open-weight models — full vendor lock-in
Opus is the most expensive frontier model at $15/$75 per 1M tokens
No native image generation capability

Cerebras

4,500+ tokens/sec on Llama 3.1 8B — fastest inference available
Sub-50ms time-to-first-token for real-time applications
Wafer-scale chip architecture eliminates GPU memory bottlenecks
Competitive pricing for the throughput delivered
OpenAI-compatible API
Very limited model selection — only a few Llama variants
No vision or multimodal support
No fine-tuning capability

Key differentiators

Anthropic

Claude 4 Opus scores highest on coding benchmarks among all frontier models, with a 200K context window and aggressive prompt caching.

Cerebras

Cerebras delivers 4,500+ tokens/sec on Llama 3.1 8B — 10× faster than any GPU provider, enabling genuinely real-time AI applications.

Frequently asked questions

Anthropic FAQs

How much does the Anthropic Claude API cost?

Claude 4 Opus costs $15/1M input and $75/1M output tokens. Claude Sonnet 4.5 is $3/$15 per 1M tokens. Claude Haiku 3.5 is the budget option at $0.80/$4.00. Prompt caching reduces input costs by up to 90%.

What is the context window for Claude models?

All Claude models support a 200,000-token context window, making them ideal for processing long documents, codebases, or multi-turn conversations without truncation.

How does Anthropic prompt caching work?

Anthropic's prompt caching lets you mark portions of your prompt (system prompts, documents, tool definitions) to be cached server-side. Cached tokens are billed at 10% of the standard input price after the first write, making repeated long-context calls dramatically cheaper.

Cerebras FAQs

How fast is Cerebras inference?

Cerebras delivers 4,500+ tokens/second on Llama 3.1 8B — roughly 10× faster than GPU-based providers like Groq (1,200 t/s) or Together AI (350 t/s). This makes it the fastest inference option available.

What is a Cerebras wafer-scale chip?

The Cerebras CS-3 chip is fabricated on a single silicon wafer rather than individual dies. This gives it 900,000 AI cores and 44GB of on-chip SRAM, eliminating the memory bandwidth bottleneck that limits GPU inference speed.

What models does Cerebras support?

Cerebras currently supports Llama 3.1 8B and 70B, and Llama 3.3 70B. The model selection is intentionally limited — Cerebras focuses on delivering extreme speed on a curated set of models rather than broad catalog coverage.

Provider resources

AnthropicClaude — safety-focused frontier AI with exceptional coding ability

Anthropic builds the Claude model family, known for long context windows (up to 200K tokens), strong coding performance, and a safety-first design philosophy. Claude 4 Opus and Sonnet lead on many coding and reasoning benchmarks. Prompt caching is available at significant discounts.

Claude 4 Opus scores highest on coding benchmarks among all frontier models, with a 200K context window and aggressive prompt caching.

CerebrasWafer-scale AI chips — 4,500 tokens/sec, the fastest inference on earth

Cerebras uses wafer-scale silicon (the CS-3 chip covers an entire silicon wafer) to deliver extraordinary inference throughput. Llama 3.1 8B runs at 4,500+ tokens/second — roughly 10× faster than GPU-based providers. This makes Cerebras uniquely suited for real-time applications, voice AI, and interactive coding assistants.

Cerebras delivers 4,500+ tokens/sec on Llama 3.1 8B — 10× faster than any GPU provider, enabling genuinely real-time AI applications.

Key strengths compared

Anthropic

  • Top coding benchmark scores (Claude 4 Opus)
  • 200K context window on all Claude models
  • Aggressive prompt caching — up to 90% discount

Cerebras

  • 4,500+ tokens/sec on Llama 3.1 8B — fastest inference available
  • Sub-50ms time-to-first-token for real-time applications
  • Wafer-scale chip architecture eliminates GPU memory bottlenecks

Provider category context

Anthropic is a frontier lab, founded in 2021. Cerebras is a inference api, founded in 2016. Anthropic as a frontier lab trains and serves its own proprietary models. Cerebras as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.

How to choose between them

Choose Anthropic if you need top coding benchmark scores (claude 4 opus). Choose Cerebras if you need 4,500+ tokens/sec on llama 3.1 8b — fastest inference available. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.