Hunyuan Pro vs MiniMax M2.7
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 Hunyuan Pro and MiniMax M2.7.
Hunyuan Pro
Hunyuan Pro (ๆททๅ Pro) is Tencent's flagship large language model developed by Tencent AI Lab, designed to power AI features across Tencent's vast ecosystem including WeChat, QQ, and enterprise cloud services. It achieves top-tier performance on Chinese-language benchmarks and strong multilingual capabilities, with native support for text, image, and video understanding. Hunyuan Pro is deployed at massive scale across Tencent's advertising, content recommendation, and customer service systems, processing billions of inference requests daily.
MiniMax M2.7
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...
Technical Specifications
| Specification | Hunyuan Pro | MiniMax M2.7 |
|---|---|---|
| Provider | Tencent | MiniMax |
| Context Window | 256,000 tokens | 204,800 tokens |
| Agent Suitability | 85/100 | N/A |
| Time to First Token (TTFT) | 320 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-11-01 | 2026-03-18 |
API Pricing Comparison
Input Price per Million Tokens
Hunyuan Pro
$0.60
MiniMax M2.7
$0.18
Output Price per Million Tokens
Hunyuan Pro
$1.20
MiniMax M2.7
$0.72
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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.
Hunyuan Pro Quirks & Gotchas
- โธMassive daily inference volume โ battle-tested at WeChat scale
- โธAPI available through Tencent Cloud โ requires Chinese enterprise account
MiniMax M2.7 Quirks & Gotchas
No developer gotchas reported.