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Celeris AI vs Cerebras: Token Pricing, Speed & Intelligence

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

Celeris AI

High-throughput frontier reasoning with Celeris-1

Celeris AI is a frontier AI lab focused on high-throughput reasoning models. Celeris-1 is their flagship model, combining strong benchmark performance on coding, math, and agentic tasks with competitive inference speed. The model supports a 256K-token context window, prompt caching, and function calling.

Agentic workflowsCode generationMathematical reasoningLong-context document analysis
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

Celeris AI

Strong reasoning and coding benchmarks
High throughput at frontier tier
Competitive prompt caching pricing
Newer provider with limited track record
Smaller ecosystem than OpenAI/Anthropic
Limited multimodal 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

Celeris AI

Celeris-1 targets the gap between o3-class reasoning quality and GPT-4o-class speed, offering frontier-tier intelligence scores at throughput rates competitive with non-reasoning models.

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

Celeris AI FAQs

What is Celeris AI?

Celeris AI is a frontier AI lab that develops high-throughput reasoning models. Their flagship Celeris-1 model targets the intersection of strong reasoning capability and fast inference.

How does Celeris-1 compare to o3 and Claude Opus?

Celeris-1 sits in the same intelligence score range as o3 and Claude Opus 5, with competitive throughput. It is priced similarly to Claude Opus 5 at $3/1M input and $15/1M output.

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

Celeris AIHigh-throughput frontier reasoning with Celeris-1

Celeris AI is a frontier AI lab focused on high-throughput reasoning models. Celeris-1 is their flagship model, combining strong benchmark performance on coding, math, and agentic tasks with competitive inference speed. The model supports a 256K-token context window, prompt caching, and function calling.

Celeris-1 targets the gap between o3-class reasoning quality and GPT-4o-class speed, offering frontier-tier intelligence scores at throughput rates competitive with non-reasoning models.

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

Celeris AI

  • Strong reasoning and coding benchmarks
  • High throughput at frontier tier
  • Competitive prompt caching pricing

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

Celeris AI is a frontier lab, founded in 2025. Cerebras is a inference api, founded in 2016. Celeris AI 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 Celeris AI if you need strong reasoning and coding benchmarks. 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.