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Cerebras vs Together AI: Token Pricing, Speed & Intelligence

Full comparison of Cerebras and Together AI — 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

Together AI

Open-source model hosting with competitive inference pricing

Together AI specialises in hosting open-weight models including the full Llama family, Mixtral, and DeepSeek variants. They offer live pricing via their public API and support fine-tuning workflows. A popular choice for teams that want open-source flexibility without managing their own GPU infrastructure.

Open-sourceFine-tuningCodingChatCost-efficiency
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

Together AI

Largest selection of open-weight models
Fine-tuning support for custom model training
OpenAI-compatible API — easy migration
Competitive pricing on Llama 3.x models
Supports 405B parameter models
No proprietary frontier models
Throughput lower than Groq/Cerebras for speed-critical apps
Fine-tuning adds complexity vs. pure inference providers

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.

Together AI

The broadest open-weight model catalog with fine-tuning support — ideal for teams that need model customisation without self-hosting.

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.

Together AI FAQs

What models does Together AI support?

Together AI hosts 100+ open-weight models including the full Llama 3.x family (8B, 70B, 405B), Mixtral, DeepSeek R1, Qwen, and many others. They also support custom fine-tuned model deployment.

How much does Together AI cost?

Llama 3.3 70B costs $0.88/1M tokens (input and output). Llama 3.1 405B is $3.50/1M tokens. Smaller models like Llama 3.2 11B Vision start at $0.18/1M tokens.

Does Together AI support fine-tuning?

Yes. Together AI offers supervised fine-tuning for Llama and other open-weight models. You can upload training data, run fine-tuning jobs, and deploy the resulting model via their inference API.

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.

Together AIOpen-source model hosting with competitive inference pricing

Together AI specialises in hosting open-weight models including the full Llama family, Mixtral, and DeepSeek variants. They offer live pricing via their public API and support fine-tuning workflows. A popular choice for teams that want open-source flexibility without managing their own GPU infrastructure.

The broadest open-weight model catalog with fine-tuning support — ideal for teams that need model customisation without self-hosting.

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

Together AI

  • Largest selection of open-weight models
  • Fine-tuning support for custom model training
  • OpenAI-compatible API — easy migration

Provider category context

Cerebras is a inference api, founded in 2016. Together AI is a inference api, founded in 2022. 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 Together AI 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.