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Cerebras vs Deep Infra: Token Pricing, Speed & Intelligence

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

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

Deep Infra

The cheapest inference API for open-weight models — Llama, Mistral, and more

Deep Infra is an inference-focused API provider specialising in open-weight models at extremely competitive prices. Consistently among the cheapest providers for Llama 3, Mistral, and DeepSeek models, making it the go-to choice for cost-sensitive production inference.

Cost-sensitive inferenceLlama 3 productionDeepSeek hostingHigh-volume batch processing
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

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

Deep Infra

Consistently lowest prices for open-weight models
Wide model catalog including Llama, Mistral, DeepSeek
OpenAI-compatible API
Fast cold start times
No rate limits on most models
No proprietary models — open-weight only
Less enterprise support than larger providers
Smaller ecosystem than Together AI or Fireworks

Key differentiators

Cerebras

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

Deep Infra

The most price-competitive inference API for open-weight models — often 30–50% cheaper than comparable providers for the same Llama or Mistral model.

Frequently asked questions

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.

Deep Infra FAQs

How cheap is Deep Infra compared to other providers?

Deep Infra is consistently among the cheapest providers for open-weight models. For example, Llama 3.1 8B is available at $0.02–0.05/1M tokens, and Llama 3.3 70B at around $0.10/1M tokens — often 30–50% below comparable providers.

What models does Deep Infra support?

Deep Infra hosts a wide range of open-weight models including the full Llama 3.x family, Mistral, Mixtral, DeepSeek V3 and R1, Qwen, and many others. The catalog is updated frequently as new models are released.

Is Deep Infra OpenAI-compatible?

Yes. Deep Infra provides an OpenAI-compatible API, so you can use the OpenAI SDK by pointing it at the Deep Infra endpoint. This makes migration straightforward.

Provider resources

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.

Deep InfraThe cheapest inference API for open-weight models — Llama, Mistral, and more

Deep Infra is an inference-focused API provider specialising in open-weight models at extremely competitive prices. Consistently among the cheapest providers for Llama 3, Mistral, and DeepSeek models, making it the go-to choice for cost-sensitive production inference.

The most price-competitive inference API for open-weight models — often 30–50% cheaper than comparable providers for the same Llama or Mistral model.

Key strengths compared

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

Deep Infra

  • Consistently lowest prices for open-weight models
  • Wide model catalog including Llama, Mistral, DeepSeek
  • OpenAI-compatible API

Provider category context

Cerebras is a inference api, founded in 2016. Deep Infra is a inference api, founded in 2023. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.

How to choose between them

Both Cerebras and Deep Infra host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.