DeepSeek vs MiniMax: Token Pricing, Speed & Intelligence
Full comparison of DeepSeek and MiniMax — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
DeepSeek
Chinese frontier lab — DeepSeek V3 and R1 at remarkably low prices
DeepSeek is a Chinese AI lab that has released highly capable open-weight models at prices far below Western competitors. DeepSeek V3 matches GPT-4 class performance at $0.27/1M input tokens, while DeepSeek R1 is a reasoning model competitive with o1 at a fraction of the cost. Both models are open-weight.
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
DeepSeek
MiniMax
Key differentiators
Frequently asked questions
DeepSeek FAQs
How much does DeepSeek cost?
DeepSeek V3 costs $0.27/1M input and $1.10/1M output tokens — roughly 10× cheaper than GPT-4o for comparable capability. DeepSeek R1 is $0.55/1M input and $2.19/1M output.
Is DeepSeek open-weight?
Yes. Both DeepSeek V3 and DeepSeek R1 are open-weight models available on Hugging Face. You can self-host them on your own GPU infrastructure, though they require significant compute (671B parameters for R1).
How does DeepSeek R1 compare to OpenAI o1?
DeepSeek R1 scores comparably to OpenAI o1 on math and coding benchmarks at a fraction of the cost. R1 is open-weight and can be self-hosted, while o1 is proprietary. R1 is available via multiple inference providers including Fireworks AI and Together AI.
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
DeepSeek — Chinese frontier lab — DeepSeek V3 and R1 at remarkably low prices
DeepSeek is a Chinese AI lab that has released highly capable open-weight models at prices far below Western competitors. DeepSeek V3 matches GPT-4 class performance at $0.27/1M input tokens, while DeepSeek R1 is a reasoning model competitive with o1 at a fraction of the cost. Both models are open-weight.
DeepSeek V3 delivers GPT-4 class intelligence at $0.27/1M input tokens — the most disruptive price-to-performance ratio in the LLM market.
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
DeepSeek
- ▸DeepSeek V3 matches GPT-4 class at $0.27/1M input — 10× cheaper
- ▸R1 reasoning model competitive with o1 at a fraction of the cost
- ▸Both V3 and R1 are open-weight — can be self-hosted
MiniMax
- ▸1M token context window
- ▸Competitive pricing
- ▸Strong multilingual performance
Provider category context
DeepSeek is a frontier lab, founded in 2023. MiniMax is a frontier lab, founded in 2021. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both DeepSeek and MiniMax are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: DeepSeek leads on deepseek v3 matches gpt-4 class at $0.27/1m input — 10× cheaper, while MiniMax leads on 1m token context window. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.