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AI Summary
Summary of DeepSeek V3 Video
- Introduction to DeepSeek V3:
- DeepSeek V3 is a 671 billion parameter model, utilizing a mixture of experts architecture.
- Each expert is approximately 37 billion in size.
- The model is trained on 15 trillion tokens and has open weights with a lenient license for commercial use.
- Performance and Features:
- Outperforms or matches Sonnet in most benchmarks.
- Based on the same architecture as DeepSeek V2.
- Features multi-token prediction, increasing inference speeds by up to two times.
- Post-trained on distilled knowledge from the R1 model, enhancing complex task performance.
- Technical Paper and Training Costs:
- The technical paper provides detailed information, including the $5.5 million training cost.
- The cost is significantly lower compared to OpenAI’s spending on testing their GPT-3 model.
- Availability and Pricing:
- Available on the DeepSeek chat platform for free with no limits.
- API costs are 0.14 without caching per 1 million input tokens, and $0.28 per 1 million output tokens until February 8th.
- After February 8th, prices will be 0.27 without caching per 1 million input tokens, and $1.10 per 1 million output tokens.
- The model is cheaper than Sonnet and offers similar results.
- Using DeepSeek V3 with Klein and Ader:
- Klein users can upgrade and configure settings for the DeepSeek or Hyperbolic API.
- Ader users can export the DeepSeek API key and use it with the model.
- The model performs well with both Klein and Ader, offering fast and accurate code generation.
- Conclusion:
- DeepSeek V3 is considered a cost-effective alternative to Sonnet, providing similar or better performance at a lower cost.
- The open-source model is giving closed-source models competition.
Detailed Instructions and URLs
- No specific CLI commands, website URLs, or detailed instructions were provided in the transcript.