DeepSeek: DeepSeek V4 Pro
DeepSeek
Capabilities
Strengths
- Exceptional 1M-token context window for long documents
- Open weights enable full data privacy and self-hosting
- Strong multi-turn conversation and reasoning capabilities
- Efficient MoE architecture balancing quality and speed
Weaknesses
- Extremely slow inference speed (34 tok/s) limits real-time applications
- No vision/multimodal capabilities
- Limited transparency on training data composition
- Reasoning features add latency overhead
Pricing
Input / 1M tokens
$0.435
Output / 1M tokens
$0.87
Context window
1,048.576k
Transparency
Open weights
10.0 / 10
Open training data
0.0 / 10
Open methodology
6.0 / 10
Licence openness
9.0 / 10
Provider disclosure
6.5 / 10
FMTI company score
N/A
Open-weight model enabling self-hosting and full data control. DeepSeek publishes model weights and some technical details, but training data sources not fully disclosed. MoE architecture and reasoning capabilities documented in research papers.
Sustainability
Inference energy
N/A
Training footprint
N/A
Provider infrastructure
5.0 / 10
DeepSeek operates in China with limited public disclosure of energy infrastructure. Open-weight design allows efficient self-hosted deployment. No official sustainability commitments published. MoE architecture with 49B activated parameters suggests moderate inference efficiency compared to dense alternatives.