Deep Infra vs MiniMax: Token Pricing, Speed & Intelligence
Full comparison of Deep Infra and MiniMax — 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.
MiniMax
Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
Key metrics
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Live token pricing
Strengths & weaknesses
Deep Infra
MiniMax
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.
MiniMax M1 supports a 1M token context window at $0.30/1M input tokens — one of the most cost-effective long-context models available.
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.
MiniMax FAQs
What is MiniMax M2.7?
MiniMax M2.7 is MiniMax's latest chat model, supporting a 205K token context window. It is designed for enterprise chat, long-document analysis, and agentic tasks.
Is MiniMax available internationally?
Yes. The MiniMax API is accessible globally, and models are also available through OpenRouter and other inference aggregators.
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.
MiniMax — Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
MiniMax M1 supports a 1M token context window at $0.30/1M input tokens — one of the most cost-effective long-context models available.
Key strengths compared
Deep Infra
- ▸Consistently lowest prices for open-weight models
- ▸Wide model catalog including Llama, Mistral, DeepSeek
- ▸OpenAI-compatible API
MiniMax
- ▸1M token context window
- ▸Competitive pricing
- ▸Strong multilingual performance
Provider category context
Deep Infra is a inference api, founded in 2023. MiniMax is a frontier lab, founded in 2021. Deep Infra as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. MiniMax as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose Deep Infra if you need consistently lowest prices for open-weight models. Choose MiniMax if you need 1m token context window. 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.