DeepSeek V4 Pro vs MiniMax M1
A side-by-side comparison of two llm models — real specs, pricing, strengths and weaknesses, and a clear verdict on which to choose. Kept current by our agents.
Quick verdict: which should you choose?
Choose DeepSeek V4 Pro if you need
- ✓Choose DeepSeek V4 Pro if you need strong coding and technical/STEM performance backed by an intelligence_index of 51.5.
- ✓Choose DeepSeek V4 Pro if you need faster outputs at 79.81 t/s and lower cost of $0.87 per million tokens.
- ✓Choose DeepSeek V4 Pro if you need an open-weight model with a slightly larger 1,048,576-token context.
- ✓Choose DeepSeek V4 Pro if you need clear, structured outputs on very long inputs.
Choose MiniMax M1 if you need
- ✓Choose MiniMax M1 if you need a proprietary model optimized for complex text workflows with 1M-token documents.
- ✓Choose MiniMax M1 if you need dedicated support for deep analysis of lengthy documents despite higher $2.2 per million token pricing.
- ✓Choose MiniMax M1 if you prefer a closed model from MiniMax for specific enterprise text-processing pipelines.
Verdict
DeepSeek V4 Pro leads on measurable dimensions with a known intelligence_index of 51.5, output speed of 79.81 t/s, and price of $0.87 per million tokens versus MiniMax M1's $2.2. Both handle million-token contexts effectively for long documents, but DeepSeek's open-weight nature and explicit coding/STEM strengths give it broader applicability where data is available. MiniMax M1 remains viable only when proprietary deployment or specific lengthy-document workflows outweigh the higher cost and missing benchmarks.
DeepSeek V4 Pro vs MiniMax M1: side by side
| Spec | DeepSeek V4 Pro | MiniMax M1 | Winner |
|---|---|---|---|
| Intelligence | 51.5 | — | Tie |
| Output speed | 80 t/s | — | Tie |
| Output price | $0.87/1M | $2.20/1M | DeepSeek V4 Pro |
| Context | 1049K | 1000K | DeepSeek V4 Pro |
| Params | — | — | Tie |
| Type | Open-weight | Proprietary | Tie |
| Provider | DeepSeek | MiniMax | Tie |
Detailed analysis
Performance
Winner: DeepSeek V4 ProDeepSeek V4 Pro provides a concrete intelligence_index of 51.5 and documented strengths in coding and STEM tasks. MiniMax M1 lists no intelligence_index and offers only general claims around lengthy documents. The facts therefore favor DeepSeek where measurable performance is required.
Pricing
Winner: DeepSeek V4 ProDeepSeek V4 Pro costs $0.87 per million tokens while MiniMax M1 costs $2.2 per million tokens. No other pricing details are supplied. DeepSeek is therefore the lower-cost option on the given data.
Speed/Context
Winner: DeepSeek V4 ProDeepSeek V4 Pro reports 79.81 t/s output speed and a 1,048,576-token context. MiniMax M1 supplies neither speed nor a precise context size beyond the rounded 1,000,000 figure and notes potential latency from large contexts. DeepSeek holds the advantage on the published metrics.
Openness
Winner: DeepSeek V4 ProDeepSeek V4 Pro is open-weight while MiniMax M1 is proprietary. This distinction is stated directly and affects deployment flexibility. No other ecosystem details are provided.
DeepSeek V4 Pro
Pros
- +Strong performance on coding tasks
- +Effective handling of very long inputs
- +Clear and structured outputs
- +Good at technical and STEM domains
Cons
- –Text-only modality
- –No real-time information access
- –Can produce hallucinations on facts
MiniMax M1
Pros
- +Supports 1M token context window
- +Strong at processing lengthy documents
- +Suitable for complex text workflows
Cons
- –Text-only modality
- –No native vision or multimodal support
- –Large context may increase latency
Summary: DeepSeek V4 Pro vs MiniMax M1
DeepSeek V4 Pro is the stronger choice for most users needing documented speed, price, coding performance, and open weights. MiniMax M1 fits only narrow cases where a proprietary 1M-context text workflow is mandatory and cost or benchmarks are secondary. Select based on whether the known metrics of DeepSeek outweigh MiniMax's unspecified profile.
Frequently asked questions
DeepSeek V4 Pro is better on all reported dimensions including intelligence_index, speed, price, and openness; MiniMax M1 lacks comparable data.