Deep Infra vs Groq: Token Pricing, Speed & Intelligence
Full comparison of Deep Infra and Groq — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
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.
Groq
LPU-powered inference — the fastest tokens per second available
Groq runs custom Language Processing Units (LPUs) that deliver dramatically higher throughput than GPU-based inference — Llama 3.3 70B reaches 750+ tokens/second on Groq, versus 100–200 on typical GPU providers. Ideal for latency-sensitive applications, real-time chat, and high-volume batch workloads.
Key metrics
—
—
—
—
—
—
—
—
—
—
—
—
Live token pricing
Strengths & weaknesses
Deep Infra
Groq
Key differentiators
The most price-competitive inference API for open-weight models — often 30–50% cheaper than comparable providers for the same Llama or Mistral model.
Groq's custom LPU chips deliver 750+ tokens/sec on Llama 3.3 70B — 4–5× faster than any GPU-based provider.
Frequently asked questions
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.
Groq FAQs
How fast is Groq inference?
Groq delivers 750+ tokens/second on Llama 3.3 70B and 1,200+ tokens/second on Llama 3.1 8B. This is 4–5× faster than typical GPU-based providers, making it ideal for real-time applications.
How much does Groq cost?
Llama 3.3 70B costs $0.59/1M input and $0.79/1M output tokens. Llama 3.1 8B is just $0.05/$0.08 per 1M tokens — among the cheapest options for a capable open-weight model.
What is a Groq LPU?
A Language Processing Unit (LPU) is Groq's custom silicon designed specifically for sequential token generation. Unlike GPUs which are optimised for parallel matrix operations, LPUs excel at the autoregressive decoding step that dominates LLM inference latency.
Provider resources
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.
The most price-competitive inference API for open-weight models — often 30–50% cheaper than comparable providers for the same Llama or Mistral model.
Groq — LPU-powered inference — the fastest tokens per second available
Groq runs custom Language Processing Units (LPUs) that deliver dramatically higher throughput than GPU-based inference — Llama 3.3 70B reaches 750+ tokens/second on Groq, versus 100–200 on typical GPU providers. Ideal for latency-sensitive applications, real-time chat, and high-volume batch workloads.
Groq's custom LPU chips deliver 750+ tokens/sec on Llama 3.3 70B — 4–5× faster than any GPU-based provider.
Key strengths compared
Deep Infra
- ▸Consistently lowest prices for open-weight models
- ▸Wide model catalog including Llama, Mistral, DeepSeek
- ▸OpenAI-compatible API
Groq
- ▸750+ tokens/sec on Llama 3.3 70B — fastest GPU-class inference
- ▸Sub-100ms time-to-first-token for real-time applications
- ▸Very competitive pricing on open-weight models
Provider category context
Deep Infra is a inference api, founded in 2023. Groq is a inference api, founded in 2016. 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 Deep Infra and Groq 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.