218 lines
27 KiB
JSON
218 lines
27 KiB
JSON
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"id": "conv_20251008_192435_112",
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"title": "搜索deepseekv3.1，qwen2.5-max，kimi-k2，gemini2.5pro的模型...",
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"content": "搜索deepseekv3.1，qwen2.5-max，kimi-k2，gemini2.5pro的模型相关信息，保证数据的准确性，主要了解其性能，做成一个精美的，设计高级的，带有可互动和方便对比的各种图表，动画和互动效果精致高级的html页面",
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"content": "我来帮您搜索这些AI模型的相关信息，并创建一个精美的交互式HTML页面进行对比展示。",
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"timestamp": "2025-10-08T19:24:55.891425"
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"content": "{\"success\": true, \"summary\": \"🔍 搜索查询: deepseek v3.1 model performance benchmarks specifications 2024\\n📅 搜索时间: 2025-10-08T19:25:03.027746\\n\\n📝 AI摘要:\\nDeepSeek V3.1 significantly outperforms V3.1-NonThinking and V3 on multiple benchmarks, especially in mathematical reasoning and coding tasks. Its \\\"thinking\\\" mode notably improves performance on complex tasks. Released in August 2025, it represents a major architectural evolution.\\n\\n---\\n\\n📊 搜索结果:\\n\\n1. DeepSeek-V3.1: Feature,architecture and benchmarks\\n 🔗 https://www.cometapi.com/what-is-deepseek-v3-1/\\n 📄 | Benchmark (metric) | V3.1-NonThinking | V3 (0324) | V3.1-Thinking | R1-0528 |\\n --- --- \\n| AIME 2024 (Pass@1) | 66.3 | 59.4 | 93.1 | 91.4 |\\n| AIME 2025 (Pass@1) | 49.8 | 51.3 | 88.4 | 87.5 |\\n| HMMT ...\\n\\n2. DeepSeek V3.1: A Technical Analysis of Key Changes ...\\n 🔗 https://www.runpod.io/blog/deepseek-v3-1-a-technical-analysis-of-key-changes\\n 📄 Performance Benchmarks and Real-World Impact\\n\\nThe performance improvements from V3-0324 to V3.1 are substantial across multiple domains. In mathematical reasoning, V3.1's thinking mode achieves AIME 2...\\n\\n3. deepseek-v3.1 Model by Deepseek-ai\\n 🔗 https://build.nvidia.com/deepseek-ai/deepseek-v3_1/modelcard\\n 📄 | | Terminal-bench (Terminus 1 framework) | 31.3 | 13.3 5.7 |\\n| Math | | | | | |\\n| | AIME 2024 (Pass@1) | 66.3 | 59.4 | 93.1 | 91.4 |\\n| | AIME 2025 (Pass@1) | 49.8 | 51.3 | 88.4 | 87.5 |\\n| |...\\n\\n4. deepseek-ai/DeepSeek-V3.1\\n 🔗 https://huggingface.co/deepseek-ai/DeepSeek-V3.1\\n 📄 | | Terminal-bench (Terminus 1 framework) | 31.3 | 13.3 5.7 |\\n| Math | | | | | |\\n| | AIME 2024 (Pass@1) | 66.3 | 59.4 | 93.1 | 91.4 |\\n| | AIME 2025 (Pass@1) | 49.8 | 51.3 | 88.4 | 87.5 |\\n| |...\\n\\n5. DeepSeek-V3.1 model now available in Amazon Bedrock\\n 🔗 https://aws.amazon.com/blogs/aws/deepseek-v3-1-now-available-in-amazon-bedrock/\\n 📄 | Benchmarks | DeepSeek-V3.1 | DeepSeek-R1-0528 |\\n --- \\n| Browsecomp | 30.0 | 8.9 |\\n| Browsecomp\\\\_zh | 49.2 | 35.7 |\\n| HLE | 29.8 | 24.8 |\\n| xbench-DeepSearch | 71.2 | 55.0 |\\n| Frames | 83.7 | 82.0 |\\n...\\n\\n6. DeepSeek V3 (Dec) - Intelligence, Performance & Price ...\\n 🔗 https://artificialanalysis.ai/models/deepseek-v3\\n 📄 Analysis of DeepSeek's DeepSeek V3 (Dec '24) and comparison to other AI models across key metrics including quality, price, performance (tokens per second & time to first token), context window & more...\\n\\n7. deepseek-ai/DeepSeek-V3\\n 🔗 https://github.com/deepseek-ai/DeepSeek-V3\\n 📄 | | Aider-Edit (Acc.) | 60.3 | 71.6 | 65.4 | 63.9 | 84.2 | 72.9 | 79.7 |\\n| | Aider-Polyglot (Acc.) 18.2 | 7.6 | 5.8 | 45.3 | 16.0 | 49.6 |\\n| Math | AIME 2024 (Pass@1) | 4.6 | 16.7 | 23.3 | 23.3 | 1...\\n\\n8. The Complete Guide to DeepSeek Models: V3, R1, V3.1 ...\\n 🔗 https://www.bentoml.com/blog/the-complete-guide-to-deepseek-models-from-v3-to-r1-and-beyond\\n 📄 DeepScaleR-1.5B-Preview is a model fine-tuned from DeepSeek-R1-Distill-Qwen-1.5B using distributed RL to scale up long-context capabilities. It improves Pass@1 accuracy on AIME 2024 by 15% (43.1% vs. ...\\n\\n9. DeepSeek-V3.1: Specifications and GPU VRAM ...\\n 🔗 https://apxml.com/models/deepseek-v3-1\\n 📄 | Benchmark | Score | Rank |\\n --- \\n| General Knowledge MMLU | 0.94 | 🥇 1 |\\n| Coding Aider Coding | 0.76 | 🥈 2 |\\n| Professional Knowledge MMLU Pro | 0.85 | 🥈 2 |\\n| Graduate-Level QA GPQA | 0.80 | 🥈 ...\\n\\n10. DeepSeek-V3.1 is here. Here's what you should know.\\n 🔗 https://bdtechtalks.substack.com/p/deepseek-v31-is-here-heres-what-you\\n 📄 Performance that rivals the proprietary giants\\n\\nEarly benchmarks show DeepSeek-V3.1 achieving a 71.6% score on the Aider coding benchmark. This result places it slightly ahead of proprietary models li...\"}",
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"content": "{\"success\": true, \"summary\": \"🔍 搜索查询: qwen 2.5 max model performance benchmarks specifications alibaba 2024\\n📅 搜索时间: 2025-10-08T19:25:12.639813\\n\\n📝 AI摘要:\\nQwen 2.5 Max outperforms other models in key benchmarks. It was launched by Alibaba in January 2025. It is a large language model developed by Alibaba Cloud.\\n\\n---\\n\\n📊 搜索结果:\\n\\n1. Qwen\\n 🔗 https://en.wikipedia.org/wiki/Qwen\\n 📄 On January 29, 2025, Alibaba launched Qwen2.5-Max. According to a blog post from Alibaba, Qwen2.5-Max outperforms other foundation models such as GPT-4o, DeepSeek-V3, and Llama \\\"Llama (language model)...\\n\\n2. Alibaba's AI model Qwen 2.5 Max emerges victorious over Deepseek\\n 🔗 https://www.notebookcheck.net/Alibaba-s-AI-model-Qwen-2-5-Max-emerges-victorious-over-Deepseek.954359.0.html\\n 📄 According to Alibaba, Qwen 2.5 Max surpasses leading AI models from Deepseek, OpenAI, and Meta in performance assessments. The model demonstrated superior results across various benchmarks, including ...\\n\\n3. [2412.15115] Qwen2.5 Technical Report - arXiv\\n 🔗 https://arxiv.org/abs/2412.15115\\n 📄 available. In addition, for hosted solutions, the proprietary models currently include two mixture-of-experts (MoE) variants: Qwen2.5-Turbo and Qwen2.5-Plus, both available from Alibaba Cloud Model St...\\n\\n4. Qwen 2.5 vs DeepSeek vs ChatGPT: Comparing performance ... - Mint\\n 🔗 https://www.livemint.com/ai/artificial-intelligence/qwen-2-5-vs-deepseek-vs-chatgpt-comparing-performance-efficiency-and-cost-openai-alibaba-ai-battle-11738169175886.html\\n 📄 ## DeepSeek: The cheaper alternative\\n\\nDeepSeek has taken the AI world by storm. Their latest model, DeepSeek-V3, and its newer iteration, the R1 model, have proven to be formidable challengers to esta...\\n\\n5. Qwen 2.5 Max API - CometAPI - All AI Models in One API\\n 🔗 https://www.cometapi.com/qwen-2-5-max-api/\\n 📄 What is Qwen? Qwen (Tongyi Qianwen) is a series of large language models (LLMs) and multimodal models developed by Alibaba Cloud, initially launched in beta version in April 2023. By July 2024, it was...\\n\\n6. In-Depth Exploration of Alibaba's Qwen 2.5 Series\\n 🔗 https://www.alibabacloud.com/blog/602121\\n 📄 Alibaba Cloud Community - September 19, 2024\\n Alibaba Cloud's Qwen 2.5 Tops OpenCompass LLM Leaderboard as the First Open-Source Champion\\n\\n Alibaba Cloud Community - October 28, 2024\\n Coding Smarter,...\\n\\n7. Qwen 2.5-Max: Features, DeepSeek V3 Comparison & More\\n 🔗 https://www.datacamp.com/blog/qwen-2-5-max\\n 📄 1. General knowledge and language understanding (MMLU, MMLU-Pro, BBH, C-Eval, CMMU): Qwen2.5-Max leads across all benchmarks in this category, scoring 87.9 on MMLU and 92.2 on C-Eval, outperforming De...\\n\\n8. Is Qwen2.5 Max better than ChatGPT-4? - Metaschool\\n 🔗 https://metaschool.so/articles/qwen2-5-max/\\n 📄 5. The LiveBench benchmark comprehensively tests the general capabilities of models. Here Qwen 2.5 Max stands out with 62.2, maintaining a slim edge over DeepSeek-V3 (60.5) and Llama-3.1 (60.3). [...]...\\n\\n9. Qwen2.5-Max: Exploring the Intelligence of Large-scale MoE Model\\n 🔗 https://qwenlm.github.io/blog/qwen2.5-max/\\n 📄 We begin by directly comparing the performance of the instruct models, which can serve for downstream applications such as chat and coding. We present the performance results of Qwen2.5-Max alongside ...\\n\\n10. Qwen2.5-Max Surpasses DeepSeek-V3 | by Cobus Greyling | Medium\\n 🔗 https://cobusgreyling.medium.com/qwen2-5-max-surpasses-deepseek-v3-c1f8dbec2508\\n 📄 When it comes to instruct models, which are optimised for real-world applications like chat and coding, Qwen2.5-Max is benchmarked against some of the best models available, including:\\n\\n DeepSeek V3 (...\"}",
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"content": "{\"success\": true, \"summary\": \"🔍 搜索查询: kimi k1.5 k2 model moonshot ai performance benchmarks 2024\\n📅 搜索时间: 2025-10-08T19:25:20.966896\\n\\n📝 AI摘要:\\nKimi K1.5 and K2 are advanced models by Moonshot AI, with K1.5 excelling in multimodal tasks and K2 focusing on agentic tasks. As of 2025, Kimi K2 ranks top in open-source models on LMSYS Arena.\\n\\n---\\n\\n📊 搜索结果:\\n\\n1. What is Kimi? Kimi k1.5 vs Kimi K2 - ScrumLaunch\\n 🔗 https://www.scrumlaunch.com/blog/kimi-k1-5-vs-kimi-k2-ai-model-comparison\\n 📄 It began with Kimi K1.5, a multimodal model that incorporates advanced reinforcement learning (RL) and is claimed to deliver state-of-the-art performance in math, code, vision, and long-context reason...\\n\\n2. Kimi K2 Instruct vs Kimi-k1.5 - AI Comparison for Builders\\n 🔗 https://theaiforger.com/models/compare/kimi-k2-instruct-vs-kimi-k1.5\\n 📄 Compare Kimi K2 Instruct (Moonshot AI) vs Kimi-k1.5 (Moonshot AI) for builders. Performance scores: Kimi K2 Instruct 38.0%, Kimi-k1.5 73.3%.\\n\\n3. Kimi-k1.5: Pricing, Context Window, Benchmarks, and More\\n 🔗 https://llm-stats.com/models/kimi-k1.5\\n 📄 Try GPT-5, GPT-OSS and more in our playground, side-by-side Kimi 1.5 is a next-generation multimodal large language model developed by Moonshot AI. It incorporates advanced reinforcement learning (RL)...\\n\\n4. [PDF] Kimi K2: Open Agentic Intelligence - arXiv\\n 🔗 https://arxiv.org/pdf/2507.20534?\\n 📄 On the LMSYS Arena leaderboard (July 17, 2025)3, Kimi K2 ranks as the top 1 open-source model and 5th overall based on over 3,000 user votes.\\n\\n5. Kimi K2: Open Agentic Intelligence - Moonshot\\n 🔗 https://moonshotai.github.io/Kimi-K2/\\n 📄 Imagine using Kimi K2 to explore remote-work salaries with the Salary Data Analysis example, where 16 IPython calls generate stats, visualizations, and an interactive webpage of insights. For pre/post...\\n\\n6. Kimi K2 is the large language model series developed by Moonshot ...\\n 🔗 https://github.com/MoonshotAI/Kimi-K2\\n 📄 [Skip to content](https://github.com/MoonshotAI/Kimi-K2#start-of-content) [View license](https://github.com/MoonshotAI/Kimi-K2/blob/main/LICENSE) * [Code](https://github.com/MoonshotAI/Kimi-K2) * ...\\n\\n7. Analysis of the Kimi K2 Open-Weight Language Model | IntuitionLabs\\n 🔗 https://intuitionlabs.ai/articles/kimi-k2-open-weight-llm-analysis\\n 📄 Moonshot AI extensively evaluated Kimi K2 against both open-source and closed-source LLMs, and the results underline K2's top-tier performance.\\n\\n8. Kimi K2, An Open-weight Agentic Model From Moonshot AI\\n 🔗 https://www.digitalocean.com/community/tutorials/kimi-k2-moonshot-ai-agentic-open-weight-model\\n 📄 Kimi K2 is a 1T parameter open-weight model designed for agentic use – achieving state-of-the-art performance in frontier knowledge, math, and coding. As a result, the K2 researchers incorporated QK-C...\\n\\n9. Kimi K2: How Moonshot AI built the Better DeepSeek. | by Devansh\\n 🔗 https://machine-learning-made-simple.medium.com/kimi-k2-how-moonshot-ai-built-the-better-deepseek-c8a22b742967\\n 📄 [Sign in](https://medium.com/m/signin?operation=login&redirect=https%3A%2F%2Fmachine-learning-made-simple.medium.com%2Fkimi-k2-how-moonshot-ai-built-the-better-deepseek-c8a22b742967&source=post_page--...\\n\\n10. Kimi K1 5 Language Model Specs & Features 2025 - BytePlus\\n 🔗 https://www.byteplus.com/en/topic/504086\\n 📄 Detailed specifications of kimi K1 5. While the term \\\"Kimi K1 5\\\" points to the impressive k1.5 model, the flagship in Moonshot AI's 2025 lineup is the Kimi K2.\"}",
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"content": "{\"success\": true, \"summary\": \"🔍 搜索查询: gemini 2.5 pro google ai model performance benchmarks specifications 2024\\n📅 搜索时间: 2025-10-08T19:25:32.658798\\n\\n📝 AI摘要:\\nGemini 2.5 Pro excels in reasoning and coding benchmarks, achieving 92.0% on AIME 2024 and 84.0% on GPQA Diamond. It has a 1 million token context window and is available via Google AI Studio. Pricing is $35 per 1,000 requests after 1,500 free daily requests.\\n\\n---\\n\\n📊 搜索结果:\\n\\n1. Gemini 2.5 Pro: Features, Tests, Access, Benchmarks & More\\n 🔗 https://www.datacamp.com/blog/gemini-2-5-pro\\n 📄 AIME 2024: Gemini 2.5 Pro leads with 92.0% for single attempt/pass@1.\\n AIME 2025: Gemini 2.5 Pro drops to 86.7% on the 2025 set of problems, and marginally leads this benchmark for single attempt/pass...\\n\\n2. Google's Gemini 2.5 Pro model tops LMArena by close to 40 points\\n 🔗 https://www.rdworldonline.com/googles-gemini-2-5-pro-model-tops-lmarena-by-40-points-outperforms-competitors-in-scientific-reasoning/\\n 📄 There were a few areas where competitors fared better (See the table at the very bottom of this article). One was GPQA diamond (with multiple attempts): Claude 3.7 Sonnet scored 84.8% compared to Gemi...\\n\\n3. Gemini 2.5 Cost and Quality Comparison | Pricing & Performance\\n 🔗 https://www.leanware.co/insights/gemini-2-5-cost-quality-comparison\\n 📄 Gemini 2.5 ProGemini 2.5 Pro is Google DeepMind’s latest multimodal model, released on March 25, 2025, as an experimental upgrade. Built on the Gemini 1.5 architecture, it features stronger reasoning,...\\n\\n4. Gemini 2.5 Pro: Benchmarks & Integration Guide for Developers\\n 🔗 https://www.helicone.ai/blog/gemini-2.5-full-developer-guide\\n 📄 | Benchmark | Gemini 2.5 Pro | OpenAI o3-mini | OpenAI GPT-4.5 | Claude 3.7 Sonnet | Grok 3 Beta | DeepSeek R1 |\\n --- --- --- \\n| Humanity's Last Exam (no tools) | 18.8% | 14.0% | 6.4% | 8.9% 8.6% |...\\n\\n5. Google Gemini 2.5 Pro: The best LLM ever | by Mehul Gupta - Medium\\n 🔗 https://medium.com/data-science-in-your-pocket/google-gemini-2-5-pro-the-best-llm-ever-172d0665336b\\n 📄 Mathematics (AIME 2024): Similar to the above, but using problems from the 2024 AIME competition. Gemini 2.5 Pro again scores the highest on single attempt (pass@1) with 92.0%, reinforcing its strong ...\\n\\n6. Gemini 2.5 Pro: A Comparative Analysis Against Its AI Rivals (2025 ...\\n 🔗 https://dirox.com/post/gemini-2-5-pro-a-comparative-analysis-against-its-ai-rivals-2025-landscape\\n 📄 > Humanity's Last Exam (HLE):Achieves 18.8%accuracy without tool use. This benchmark testsexpert-level knowledge and reasoningacross diverse fields.Gemini 2.5 Pro's score significantly leads competito...\\n\\n7. Gemini 2.5: Our most intelligent AI model\\n 🔗 https://blog.google/technology/google-deepmind/gemini-model-thinking-updates-march-2025/\\n 📄 Gemini 2.5 Pro is state-of-the-art across a range of benchmarks requiring advanced reasoning. Without test-time techniques that increase cost, like majority voting, 2.5 Pro leads in math and science b...\\n\\n8. Gemini 2.5 Pro Preview: even better coding performance\\n 🔗 https://developers.googleblog.com/en/gemini-2-5-pro-io-improved-coding-performance/\\n 📄 Gemini 2.5 Pro delivers state-of-the-art video understanding, scoring 84.8% on the VideoMME benchmark. Combining this with coding enables new flows that were previously not possible with previous vers...\\n\\n9. Gemini 2.5 Pro - Google DeepMind\\n 🔗 https://deepmind.google/models/gemini/pro/\\n 📄 | Code generation LiveCodeBench (UI: 1/1/2025-5/1/2025) | | 33.7% | 34.3% | 41.1% | 55.4% | 69.0% |\\n| Code editing Aider Polyglot | | 26.7% | 27.1% | 44.0% | 56.7% | 82.2% |\\n| Agentic coding SWE-ben...\\n\\n10. Gemini 2.5 Pro: A Developer's Guide to Google's Most ...\\n 🔗 https://dev.to/brylie/gemini-25-pro-a-developers-guide-to-googles-most-advanced-ai-53lf\\n 📄 | Benchmark | Gemini 2.5 Pro | GPT-4.5 | Claude 3.7 Sonnet | Significance for Developers |\\n --- --- \\n| SWE-Bench Verified | 63.8% | 38.0% | 70.3% | Real-world coding task performance |\\n| LiveCodeBenc...\"}",
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"content": "现在让我搜索更多关于模型对比和价格的信息：",
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"content": "{\"success\": true, \"summary\": \"🔍 搜索查询: \\\"AI model comparison\\\" \\\"deepseek v3.1\\\" \\\"qwen 2.5 max\\\" \\\"kimi k2\\\" \\\"gemini 2.5 pro\\\" pricing benchmarks 2024\\n📅 搜索时间: 2025-10-08T19:25:44.990958\\n\\n📝 AI摘要:\\nDeepSeek V3.1 and Qwen 2.5 Max are competitive models with DeepSeek V3.1 priced at $0.25 per million tokens and Qwen 2.5 Max at $0.38 per million tokens. Both models show strong performance in benchmarks and coding tasks.\\n\\n---\\n\\n📊 搜索结果:\\n\\n1. Artificial Analysis DeepSeek V3.1 (Non-reasoning) vs Kimi K2: Model Comparison\\n 🔗 https://artificialanalysis.ai/models/comparisons/deepseek-v3-1-vs-kimi-k2\\n 📄 | Gemini 2.0 Flash Thinking Experimental (Jan '25) | Google | Proprietary | 1m | |\\n| Gemini 2.5 Flash Preview (Reasoning) | Google | Proprietary | 1m | |\\n| Gemini 2.0 Flash Thinking Experimental (De...\\n\\n2. Index.dev Top 6 Chinese AI Models Like DeepSeek (LLMs) You Should Know\\n 🔗 https://www.index.dev/blog/chinese-ai-models-deepseek\\n 📄 DROP Benchmark: It achieved a score of 91.6, outperforming Llama 3.1's 88.7.\\n Codeforces Benchmark: DeepSeek V3 scored 51.6, indicating strong code generation capabilities.\\n MATH-500 Benchmark: It...\\n\\n3. Artificial Analysis Comparison of AI Models across Intelligence, Performance, Price | Artificial Analysis\\n 🔗 https://artificialanalysis.ai/models\\n 📄 | Image 188: DeepSeek logoDeepSeek R1 Distill Llama 70B | DeepSeek | Open | 128k | ModelAPI Providers |\\n| Image 189: DeepSeek logoDeepSeek R1 Distill Qwen 32B | DeepSeek | Open | 128k | ModelAPI Provi...\\n\\n4. Clarifai OpenAI GPT‑OSS Benchmarks: How It Compares to GLM‑4.5, Qwen3, DeepSeek, and Kimi K2\\n 🔗 https://www.clarifai.com/blog/openai-gpt-oss-benchmarks-how-it-compares-to-glm-4.5-qwen3-deepseek-and-kimi-k2\\n 📄 | Benchmark | GPT‑OSS‑120b (High) | GLM‑4.5 | Qwen3 Thinking | DeepSeek R1 | Kimi K2 |\\n --- --- --- |\\n| MMLU‑Pro | 90.0% | 84.6% | 84.4% | 85.0% | 81.1% |\\n| AIME 2024 | 96.6% (with tools) | ~91% | ~...\\n\\n5. Appy pie Automate Top AI Models Compared: Grok-3, DeepSeek R1, OpenAI o3-mini, Claude 3.7, Qwen 2.5 & Gemini 2.0\\n 🔗 https://www.appypieautomate.ai/blog/comparison/grok-vs-deepseek-vs-openai-vs-claude-vs-qwen-vs-gemini\\n 📄 AI Automation\\n Pricing\\n Contact Sales\\n\\n Try 7 Days Free Trial\\n \\n Join\\n Log in\\n\\n1. Home\\n2. Blog\\n3. Comparison\\n\\nImage 2: Comparison of Grok vs. DeepSeek vs. OpenAI vs. Claude vs. Qwe...\\n\\n6. DeepSeek - Wikipedia\\n 🔗 https://en.wikipedia.org/wiki/DeepSeek\\n 📄 The cost has been discussed( and called misleading, because it covers only parts of the true cost.(\\n\\nBenchmark tests show that V3 outperformed Llama \\\"Llama (language model)\\\") 3.1 and Qwen 2.5 while ma...\\n\\n7. Artificial Analysis LLM Leaderboard - Comparison of over 100 AI models from OpenAI, Google, DeepSeek & others | Artificial Analysis\\n 🔗 https://artificialanalysis.ai/leaderboards/models\\n 📄 | GLM-4.6 | 200k | Image 40: Z AI | 56 | $0.96 | 51 | 0.72 | ModelProviders |\\n| Qwen3 Max | 262k | Image 41: Alibaba | 55 | $2.40 | 34 | 1.64 | ModelProviders |\\n| Gemini 2.5 Flash (Sep) | 1m | Image 4...\\n\\n8. Analytics Vidhya Qwen2.5-Max vs DeepSeek-R1 vs Kimi k1.5: Which is the Best?\\n 🔗 https://www.analyticsvidhya.com/blog/2025/02/qwen2-5-max-vs-deepseek-r1-vs-kimi-k1-5-2/\\n 📄 3. MMLU: This benchmark tests multi-subject knowledge and language understanding across various domains (mathematics, sciences, humanities, etc.). Qwen2.5-Max leads over DeepSeek R1, showing a better ...\"}",
|
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"timestamp": "2025-10-08T19:25:44.997544",
|
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"tool_call_id": "web_search:4",
|
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"name": "web_search"
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "现在让我创建一个精美的交互式HTML页面来展示这些AI模型的对比信息：",
|
||
"timestamp": "2025-10-08T19:25:48.331859"
|
||
},
|
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{
|
||
"role": "assistant",
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"content": "",
|
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"timestamp": "2025-10-08T19:25:48.339237",
|
||
"tool_calls": [
|
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{
|
||
"id": "create_file:5",
|
||
"index": 0,
|
||
"type": "function",
|
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"function": {
|
||
"name": "create_file",
|
||
"arguments": "{\"path\": \"ai_models_comparison/index.html\", \"file_type\": \"html\", \"annotation\": \"AI模型对比展示页面 - 包含DeepSeek V3.1、Qwen 2.5 Max、Kimi K2、Gemini 2.5 Pro的详细对比\"}"
|
||
}
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"success\": true, \"path\": \"ai_models_comparison/index.html\", \"size\": 0, \"message\": \"已创建空文件: ai_models_comparison/index.html。请使用 append_to_file 追加正文内容，或使用 modify_file 进行小范围替换。\"}",
|
||
"timestamp": "2025-10-08T19:25:50.170534",
|
||
"tool_call_id": "create_file:5",
|
||
"name": "create_file"
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"timestamp": "2025-10-08T19:25:52.260911",
|
||
"tool_calls": [
|
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{
|
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"id": "append_to_file:6",
|
||
"index": 0,
|
||
"type": "function",
|
||
"function": {
|
||
"name": "append_to_file",
|
||
"arguments": "{\"path\": \"ai_models_comparison/index.html\", \"reason\": \"创建完整的AI模型对比HTML页面，包含交互式图表和动画效果\"}"
|
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}
|
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}
|
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]
|
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},
|
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{
|
||
"role": "tool",
|
||
"content": "{\"success\": true, \"awaiting_content\": true, \"path\": \"ai_models_comparison/index.html\", \"message\": \"\\n请按照以下格式输出需要追加到文件的完整内容，禁止输出任何解释性文字：\\n<<<APPEND:ai_models_comparison/index.html>>>\\n(在此行之后紧接着写入要追加的全部内容，可包含多行代码)\\n<<<END_APPEND>>>\\n若追加完成后仍需继续写入，请再次调用 append_to_file。\"}",
|
||
"timestamp": "2025-10-08T19:25:54.075642",
|
||
"tool_call_id": "append_to_file:6",
|
||
"name": "append_to_file"
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "已向 ai_models_comparison/index.html 追加 565 行（17962 字节）。未检测到结束标识，已在输出结束处完成写入，请补充<<<END_APPEND>>>。",
|
||
"timestamp": "2025-10-08T19:27:43.919943"
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"success\": true, \"path\": \"ai_models_comparison/index.html\", \"lines\": 565, \"bytes\": 17962, \"forced\": true, \"message\": \"已向 ai_models_comparison/index.html 追加 565 行（17962 字节）。未检测到结束标识，已在输出结束处完成写入，请补充<<<END_APPEND>>>。\"}",
|
||
"timestamp": "2025-10-08T19:27:43.928920",
|
||
"tool_call_id": "append_to_file:6",
|
||
"name": "append_to_file"
|
||
},
|
||
{
|
||
"role": "system",
|
||
"content": "刚才向 ai_models_comparison/index.html 追加的内容未检测到 <<<END_APPEND>>>，请继续输出剩余部分，并以 <<<END_APPEND>>> 正确闭合。",
|
||
"timestamp": "2025-10-08T19:27:43.940105"
|
||
}
|
||
],
|
||
"metadata": {
|
||
"project_path": "/Users/jojo/Desktop/agents/正在修复中/agent_kimi_源码备份/project",
|
||
"thinking_mode": true,
|
||
"total_messages": 21,
|
||
"total_tools": 15,
|
||
"status": "active"
|
||
},
|
||
"token_statistics": {
|
||
"total_input_tokens": 147725,
|
||
"total_output_tokens": 630,
|
||
"updated_at": "2025-10-08T19:55:08.316689"
|
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}
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} |