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deepseek-ai/DeepSeek-Math-V2
默认分支 main · commit 665c8407 · 扫描时间 2026/5/28 14:32:38
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行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 deepseek-ai/DeepSeek-Math-V2 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。
行动计划 — 可复制粘贴的修复
2 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。
- highabout#1Add a concise repository description
原因:
复制粘贴的修复DeepSeekMath-V2 is a Mixture-of-Experts (MoE) large language model specifically designed and optimized for advanced mathematical reasoning and verifiable problem-solving.
- mediumreadme#2Strengthen the README's opening statement for immediate positioning
原因:
当前Large language models have made significant progress in mathematical reasoning, which serves as an important testbed for AI and could impact scientific research if further advanced. By scaling reasoning with reinforcement learning that rewards correct final answers, LLMs have improved from poor performance to saturating quantitative reasoning competitions like AIME and HMMT in one year. However, this approach faces fundamental limitations. Pursuing higher final answer accuracy doesn't address a key issue: correct answers don't guarantee correct reasoning. Moreover, many mathematical tasks like theorem proving require rigorous step-by-step derivation rather than numerical answers, making final answer rewards inapplicable. To push the limits of deep reasoning, we believe it is necessary to verify the comprehensiveness and rigor of mathematical reasoning. Self-verification is particularly important for scalin
复制粘贴的修复DeepSeekMath-V2 is a state-of-the-art Mixture-of-Experts (MoE) large language model specifically engineered for advanced mathematical reasoning and self-verifiable problem-solving. Unlike traditional approaches focused solely on final answer accuracy, DeepSeekMath-V2 emphasizes comprehensive and rigorous step-by-step derivation, crucial for complex tasks like theorem proving and ensuring the correctness of reasoning itself.
本次扫描解析到的品类 GEO 通道:google/gemini-2.5-flash, deepseek/deepseek-v4-flash
品类可见性 — 真正的 GEO 测试
向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?
各模型使用同一组问题 — 切换标签对比回答与排名。
- Wolfram Alpha · 被推荐 2 次
- GPT-4 · 被推荐 1 次
- Claude 3 Opus · 被推荐 1 次
- AlphaGeometry · 被推荐 1 次
- Minerva by Google · 被推荐 1 次
- 品类问题Which AI models excel at complex mathematical reasoning and solution verification?你:未被推荐AI 推荐顺序:
- GPT-4
- Claude 3 Opus
- AlphaGeometry
- Minerva by Google
- Llama 3
- Wolfram Alpha
AI 推荐了 6 个替代方案,却始终没点名 deepseek-ai/DeepSeek-Math-V2。这就是要补上的差距。
查看 AI 完整回答
- 品类问题Need an advanced language model for robust mathematical problem-solving with verifiable steps.你:未被推荐AI 推荐顺序:
- OpenAI GPT-4
- Google Gemini Advanced
- Anthropic Claude 3 Opus
- Wolfram Alpha
- Meta Llama 3
AI 推荐了 5 个替代方案,却始终没点名 deepseek-ai/DeepSeek-Math-V2。这就是要补上的差距。
查看 AI 完整回答
客观检查
针对 AI 引擎最看重的元数据信号的规则审计。
- Metadata completenessfail
建议:
- README presencepass
自指检查
当被直接问到你时,AI 是否还知道你的仓库存在?
- Compared to common alternatives in this category, what is the core differentiator of deepseek-ai/DeepSeek-Math-V2?passAI 未点名 deepseek-ai/DeepSeek-Math-V2 —— 很可能在说另一个项目
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- If a team adopts deepseek-ai/DeepSeek-Math-V2 in production, what risks or prerequisites should they evaluate first?passAI 明确点名了 deepseek-ai/DeepSeek-Math-V2
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- In one sentence, what problem does the repo deepseek-ai/DeepSeek-Math-V2 solve, and who is the primary audience?passAI 明确点名了 deepseek-ai/DeepSeek-Math-V2
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
嵌入你的 GEO 徽章
把这个徽章贴进 deepseek-ai/DeepSeek-Math-V2 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。
[](https://repogeo.com/zh/r/deepseek-ai/DeepSeek-Math-V2)<a href="https://repogeo.com/zh/r/deepseek-ai/DeepSeek-Math-V2"><img src="https://repogeo.com/badge/deepseek-ai/DeepSeek-Math-V2.svg" alt="RepoGEO" /></a>订阅 Pro,解锁深度诊断
deepseek-ai/DeepSeek-Math-V2 — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。
- 深度报告每月 10 次
- 无品牌品类查询5,轻量 2
- 优先行动项8,轻量 3