Doubao Pro vs MiniMax M2
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 Doubao Pro and MiniMax M2.
Doubao Pro
Doubao Pro (่ฑๅ Pro) is ByteDance's flagship large language model, powering the Doubao AI assistant used by over 100 million monthly active users in China. Built by ByteDance's Seed team, Doubao Pro achieves top-tier results on Chinese-language benchmarks, excelling at long-context understanding, multimodal reasoning, and creative writing. Its architecture is optimized for the massive scale of ByteDance's inference infrastructure, enabling cost-efficient deployment across Douyin, TikTok, and enterprise API customers via Volcano Engine.
MiniMax M2
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Technical Specifications
| Specification | Doubao Pro | MiniMax M2 |
|---|---|---|
| Provider | ByteDance | MiniMax |
| Context Window | 256,000 tokens | 204,800 tokens |
| Agent Suitability | 86/100 | N/A |
| Time to First Token (TTFT) | 300 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-01-15 | 2025-10-23 |
API Pricing Comparison
Input Price per Million Tokens
Doubao Pro
$0.80
MiniMax M2
$0.26
Output Price per Million Tokens
Doubao Pro
$1.60
MiniMax M2
$1.02
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Doubao Pro Quirks & Gotchas
- โธMassive user base โ one of the most deployed Chinese models in production
- โธAPI available through Volcano Engine โ requires Chinese enterprise registration
MiniMax M2 Quirks & Gotchas
No developer gotchas reported.