DeepSeek R1 - o1 Performance, Completely Open-Source - Video Insight
DeepSeek R1 - o1 Performance, Completely Open-Source - Video Insight
Matthew Berman
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Deep Seek R1, an open-source AI model, rivals OpenAI's offerings, promising lower costs and spurring further innovation in the field.

Deep Seek R1, an open-source AI model, has been launched, demonstrating impressive performance comparable to OpenAI's commercial models. It offers a complete package of open weights and an MIT license, allowing unrestricted use and promotion of creativity in AI development. As competition intensifies, this new model showcases the potential of open-source initiatives to challenge statistically advanced systems while keeping costs significantly lower, marking an important shift in the AI landscape and foreshadowing widespread developments in open-source thinking models.


Content rate: A

The content is highly informative, provides numerous well-supported claims backed by detailed evidence, and encourages innovative thought in the field of AI. It thoroughly explains the significance of the developments in open-source AI models and their potential impact on the industry.

AI OpenSource Technology Model Benchmark

Claims:

Claim: Deep Seek R1 outperforms OpenAI's models in many benchmarks.

Evidence: Statistics provided from various benchmarks show Deep Seek R1 performing better or on par with OpenAI's models across multiple testing scenarios.

Counter evidence: However, some benchmarks indicate OpenAI's 01 model is still superior in specific areas, suggesting the performance gap narrows rather than closes.

Claim rating: 8 / 10

Claim: The open-source model will see a surge in similar technologies emerging due to its accessible nature.

Evidence: The speaker suggests that the success of Deep Seek R1 sets a roadmap for other companies, indicating that it's now demonstrated feasible open-source alternatives to closed-source models.

Counter evidence: Not all companies may have the resources or expertise to replicate the success of Deep Seek R1, potentially limiting the expected influx of similar models.

Claim rating: 7 / 10

Claim: Deep Seek R1 is significantly cheaper than OpenAI's pricing models.

Evidence: Pricing analysis reveals that the input and output costs for Deep Seek R1 are markedly lower than those of its closed-source counterparts, etc.

Counter evidence: While the base cost is lower, additional features or capabilities may still require higher expenses in the long run, potentially offsetting initial savings.

Claim rating: 9 / 10

Model version: 0.25 ,chatGPT:gpt-4o-mini-2024-07-18

### Key Facts and Information About Deep Seek R1 Model 1. **Open Source Release**: Deep Seek R1 is a fully open-source model with open weights, licensed under MIT, allowing for commercial use and modification. 2. **Benchmark Performance**: - Deep Seek R1 competes well with OpenAI’s 01 model: - Beats OpenAI 01 on AIM 2024 Benchmark. - Comparable performance on Codeforces and SWE Bench. - Slightly behind OpenAI 01 on certain math benchmarks. 3. **Pricing**: - Deep Seek R1's API costs significantly less than OpenAI's offerings. - Input API price: $0.14 per million tokens (compared to $7.5 for OpenAI). - Output price: $2.19 per million tokens (versus $60 for OpenAI). 4. **Distilled Versions**: Multiple distilled versions of Deep Seek R1 are available (models of 1.5B, 7B, 14B, 32B, and a 70B version). 5. **Distinct Reasoning Style**: The model exhibits a human-like thought process in reasoning, often checking and correcting its steps before arriving at conclusions. 6. **Learning Methodology**: - Uses reinforcement learning without human feedback to solve problems. - Incorporates multi-stage training to enhance reasoning capabilities. 7. **Anticipated Model Evolution**: - Following the release timeline of similar models, there is speculation about the emergence of Deep Seek R3 within three months, which might offer further advancements. 8. **Comparative Evaluation**: - Deep Seek R1 is shown to perform better than various models from CLA, GPT-40, and is being compared favorably across several benchmarks. 9. **Flexible Application**: - The model can be accessed via its API for fine-tuning and distillation, making it adaptable to various use cases. 10. **Future Developments**: The model’s success may inspire a wave of new open-source thinking models following the demonstrated capabilities and roadmap provided by Deep Seek. ### Conclusion Deep Seek R1’s release marks a significant milestone in open-source AI, showcasing competitive performance against prominent closed-source models, while enhancing accessibility and affordability for developers and businesses.