Cerebras vs FastInfra: Token Pricing, Speed & Intelligence
Full comparison of Cerebras and FastInfra — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Cerebras
CS-4 wafer-scale — high-throughput inference on GPT OSS 120B and Qwen 3.8 27B
Cerebras uses wafer-scale silicon (the CS-4 chip) to deliver high-throughput inference significantly faster than conventional GPU systems. The Developer tier provides self-serve access; Enterprise tier adds production capacity, custom model weights, fine-tuning, and dedicated support. Available on AWS Marketplace, OpenRouter, HuggingFace, and Vercel. Check cerebras.ai/pricing for current rates and any free-credit offers.
FastInfra
Inference platform + GPU pods — 785+ models, Amazon Nova, H200 capacity
FastInfra is a hybrid inference platform combining a model router (785+ models) with its own H200 GPU capacity. It offers Amazon Nova Lite and Nova Micro at very competitive rates, with prepaid credits from $5. Part inference router, part dedicated GPU cloud.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Cerebras
FastInfra
Key differentiators
Cerebras CS-4 wafer-scale silicon delivers high-throughput inference on GPT OSS 120B and Qwen 3.8 27B — significantly faster than conventional GPU systems, enabling real-time agentic workflows and interactive AI.
Hybrid inference platform with 785+ models via router and own H200 capacity, offering Amazon Nova at very competitive rates.
Frequently asked questions
Cerebras FAQs
How fast is Cerebras inference?
Cerebras delivers significantly higher throughput than conventional GPU-based providers on GPT OSS 120B and Qwen 3.8 27B, enabling real-time agentic workflows and interactive AI applications. Check cerebras.ai for current benchmark figures.
What is the Cerebras CS-4 chip?
The CS-4 is Cerebras's latest wafer-scale chip, 58× larger than a GPU. It provides 900,000+ AI cores and massive on-chip SRAM, eliminating the memory bandwidth bottleneck that limits GPU inference speed.
What models does Cerebras support?
Cerebras supports GPT OSS 120B and Qwen 3.8 27B on the Developer tier. Enterprise adds access to all models including production and preview models. Check cerebras.ai/pricing for current rates.
FastInfra FAQs
What is FastInfra?
FastInfra is a hybrid inference platform combining a 785+ model router with its own H200 GPU capacity. It offers Amazon Nova Lite ($0.06/$0.25 per 1M tokens) and Nova Micro ($0.04/$0.15), with prepaid credits from $5. See fastinfra.ai/pricing for current rates.
Does FastInfra have its own GPU capacity?
Yes. FastInfra operates its own H200 GPU infrastructure alongside a model router, so some models run on dedicated capacity rather than being routed to third-party providers.
Provider resources
Cerebras — CS-4 wafer-scale — high-throughput inference on GPT OSS 120B and Qwen 3.8 27B
Cerebras uses wafer-scale silicon (the CS-4 chip) to deliver high-throughput inference significantly faster than conventional GPU systems. The Developer tier provides self-serve access; Enterprise tier adds production capacity, custom model weights, fine-tuning, and dedicated support. Available on AWS Marketplace, OpenRouter, HuggingFace, and Vercel. Check cerebras.ai/pricing for current rates and any free-credit offers.
Cerebras CS-4 wafer-scale silicon delivers high-throughput inference on GPT OSS 120B and Qwen 3.8 27B — significantly faster than conventional GPU systems, enabling real-time agentic workflows and interactive AI.
FastInfra — Inference platform + GPU pods — 785+ models, Amazon Nova, H200 capacity
FastInfra is a hybrid inference platform combining a model router (785+ models) with its own H200 GPU capacity. It offers Amazon Nova Lite and Nova Micro at very competitive rates, with prepaid credits from $5. Part inference router, part dedicated GPU cloud.
Hybrid inference platform with 785+ models via router and own H200 capacity, offering Amazon Nova at very competitive rates.
Key strengths compared
Cerebras
- GPT OSS 120B: high-throughput inference on CS-4 wafer-scale silicon
- Qwen 3.8 27B: fast efficient-tier inference
- CS-4 chip: 58× larger than GPUs, purpose-built for AI inference
- Limited model selection vs. Together AI or Fireworks
- No vision or multimodal support
FastInfra
- 785+ models via router — broad catalog coverage
- Own H200 GPU capacity for low-latency inference
- Very competitive Amazon Nova Lite ($0.06/$0.25) and Nova Micro ($0.04/$0.15) rates
- Newer provider — limited ecosystem integrations and third-party reviews
- Hybrid router/own-capacity model means latency may vary by model
Key weaknesses compared
Cerebras
- Limited model selection vs. Together AI or Fireworks
- No vision or multimodal support
- No fine-tuning on Developer tier
FastInfra
- Newer provider — limited ecosystem integrations and third-party reviews
- Hybrid router/own-capacity model means latency may vary by model
- Limited benchmark transparency
Provider category context
Cerebras is a inference api, founded in 2016. FastInfra is a inference api, founded in 2024. 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 FastInfra 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.