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Quick Comparison
Here’s a table of spec comparsion for the most current model:
| Feature | Claude 3.5 Sonnet | OpenAI o1 | DeepSeek R1 |
|---|---|---|---|
| Model Size | Unknown | 2.8T parameters (unconfirmed) | 671B parameters (37B active per token) |
| Context Window | 200K tokens | 128K tokens | 128K tokens |
| Max Output | 4K tokens | 32K tokens | 32K tokens |
| Vision Capability | Yes | No | No |
| Knowledge Cutoff | April 2024 | Oct 2023 | Unknown |
| Cost (Input) | $3/1M tokens | $15/1M tokens | $0.55/1M tokens |
| Cost (Output) | $15/1M tokens | $60/1M tokens | $2.19/1M tokens |
| Open Source | No | No | Yes (MIT License) |
| Hallucination Rate | Unknown (Lower than previous models | Unknown (Lower than GPT-4 (0.44 on SimpleQA) | Unknown (4x higher than DeepSeek V3 |
| Performance | 40% success on autonomy tasks | High performance on AIME, Codeforces, GPQA-Diamond | Comparable to o1 on math and coding tasks |
| Special Features | Constitutional AI framework, near-perfect recall | Advanced reasoning capabilities, high accuracy on complex tasks | Resource-efficient MoE architecture, self-discovering reasoning strategies |
(updated on “2025-02-05T144338”, generated using perplexity)
Parameters to Compare
Context
- context window:
- How much information can you feed into the chatbot at once?
- This is typically measured in words or tokens.
- context remainment:
- How many back-and-forth exchanges can occur before the chatbot begins to forget earlier parts of the conversation?
- What’s the maximum conversation length it can effectively maintain?
Reliability
- hallucination:
- How accurate is the chatbot’s information?
- Can it resist confirming biased or incorrect assumptions in questions?
- Does it generate false or misleading information while presenting it as fact?
- internet access :
- Can the bot retrieve real-time information from external sources?
- Does it automatically access websites, academic papers, or other online resources when needed ?
- source transparency :
- Does the bot cite its sources?
- Is it clear about where its information comes from?
- Does it explain the basis for its responses?
Usability
- writting tone:
- How natural and human-like is the bot’s communication?
- Can it adjust its tone to match different situations?
- multi-model:
- Can the bot process different types of input beyond text?
- Does it handle documents (PDF, DOCX), images, audio, and video?
- Can it effectively use information from these various formats in its responses?
- response freshness:
- How consistent are the bot’s responses to identical questions?
- Does it offer helpful variations in its answers?
- legal liability:
- Does the bot recognize and refuse inappropriate requests?
- How does it handle sensitive topics (political, legal, or ethical issues)?
- Are there clear guidelines about what it won’t discuss?
Other
- community:
- Is there an active community developing extensions or plugins?
- Are there readily available tools to enhance the bot’s capabilities using initial prompting? and can the bot be customized for specific professional needs (like writing, teaching, or specialized fields) ?