DeepSeek V3.1 vs MiniMax M2-her
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek V3.1 and MiniMax M2-her.
DeepSeek V3.1
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...
MiniMax M2-her
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message...
Technical Specifications
| Specification | DeepSeek V3.1 | MiniMax M2-her |
|---|---|---|
| Provider | DeepSeek | MiniMax |
| Context Window | 163,840 tokens | 65,536 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-08-21 | 2026-01-23 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.1
$0.21
MiniMax M2-her
$0.30
Output Price per Million Tokens
DeepSeek V3.1
$0.79
MiniMax M2-her
$1.20
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
DeepSeek V3.1 Quirks & Gotchas
No developer gotchas reported.
MiniMax M2-her Quirks & Gotchas
No developer gotchas reported.