DeepSeek-V4-Pro-Max vs MiniMax M3
DeepSeek-V4-Pro-Max and MiniMax M3 are closely matched at 43.5 and 41.4 on the LLM Stats Score. MiniMax M3 is 3.8x cheaper per token.
DeepSeek · MiniMax · Updated for 2026
Which is better?
DeepSeek-V4-Pro-Max and MiniMax M3 are closely matched on the overall LLM Stats Score at 43.5 and 41.4.
The models split the 6 individual benchmarks reported for both models evenly.
On price, MiniMax M3 is roughly 3.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Pro-Max also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-Max
- you process long inputs — it offers a 1,048,576 token context window
Choose MiniMax M3
- cost matters — it's about 3.8x cheaper per token
- you want the most recent training data — it shipped Jun 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for DeepSeek-V4-Pro-Max · 35 for MiniMax M3
DeepSeek-V4-Pro-Max outperforms in 3 benchmarks (FrontierCode 1.1, LiveBench, SWE-Bench Verified), while MiniMax M3 is better at 3 benchmarks (BrowseComp, MCP Atlas, SWE-Bench Pro).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-Max ($1.60/1M tokens) is 5.3x more expensive than MiniMax M3 ($0.30/1M tokens).
For output processing, DeepSeek-V4-Pro-Max ($3.20/1M tokens) is 2.7x more expensive than MiniMax M3 ($1.20/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than MiniMax M3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-Max has 1172.0B more parameters than MiniMax M3, making it 273.8% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-Max accepts 1,048,576 input tokens compared to MiniMax M3's 512,000 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
MiniMax M3 supports multimodal inputs, whereas DeepSeek-V4-Pro-Max does not.
MiniMax M3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-Max
MiniMax M3
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-Max was released on 2026-04-23, while MiniMax M3 was released on 2026-06-01.
MiniMax M3 is 1 month newer than DeepSeek-V4-Pro-Max.
Apr 23, 2026
4 months ago
Jun 1, 2026
3 months ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Pro-Max is available from Novita, DeepInfra, DeepSeek, Fireworks, Together. MiniMax M3 is available from Fireworks, MiniMax, Novita, Together.
DeepSeek-V4-Pro-Max
MiniMax M3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-Max and MiniMax M3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-Max vs MiniMax M3.