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feat: ParamHub参数百科Python版

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功能:
- 模型数据库 (12个模型)
- GPU数据库 (10个GPU)
- CPU数据库 (8个CPU)
- 显存计算器
- 对比工具
- 知识库
This commit is contained in:
hubian
2026-04-09 01:59:09 +08:00
commit 7d90603b23
15 changed files with 1742 additions and 0 deletions
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[
{"id": "epyc9654", "name": "AMD EPYC 9654", "manufacturer": "AMD", "architecture": "Zen 4", "cores": 96, "threads": 192, "base_clock_ghz": 2.4, "boost_clock_ghz": 3.7, "l3_cache_mb": 384, "tdp_watts": 360, "price_usd": 11000, "release_year": 2022, "description": "AMD顶级服务器CPU，96核心"},
{"id": "epyc9554", "name": "AMD EPYC 9554", "manufacturer": "AMD", "architecture": "Zen 4", "cores": 64, "threads": 128, "base_clock_ghz": 3.1, "boost_clock_ghz": 3.8, "l3_cache_mb": 256, "tdp_watts": 360, "price_usd": 6800, "release_year": 2022, "description": "64核心高性能服务器CPU"},
{"id": "epyc9454", "name": "AMD EPYC 9454", "manufacturer": "AMD", "architecture": "Zen 4", "cores": 48, "threads": 96, "base_clock_ghz": 2.75, "boost_clock_ghz": 3.8, "l3_cache_mb": 192, "tdp_watts": 290, "price_usd": 4100, "release_year": 2022, "description": "48核心服务器CPU"},
{"id": "xeonw9359x", "name": "Intel Xeon w9-3595X", "manufacturer": "Intel", "architecture": "Sapphire Rapids", "cores": 56, "threads": 112, "base_clock_ghz": 1.9, "boost_clock_ghz": 4.8, "l3_cache_mb": 105, "tdp_watts": 350, "price_usd": 6200, "release_year": 2023, "description": "Intel顶级工作站CPU"},
{"id": "xeonw5345", "name": "Intel Xeon w5-3435", "manufacturer": "Intel", "architecture": "Sapphire Rapids", "cores": 24, "threads": 48, "base_clock_ghz": 3.1, "boost_clock_ghz": 4.7, "l3_cache_mb": 45, "tdp_watts": 230, "price_usd": 950, "release_year": 2023, "description": "中端工作站CPU"},
{"id": "ryzen97950x", "name": "AMD Ryzen 9 7950X", "manufacturer": "AMD", "architecture": "Zen 4", "cores": 16, "threads": 32, "base_clock_ghz": 4.5, "boost_clock_ghz": 5.7, "l3_cache_mb": 64, "tdp_watts": 170, "price_usd": 550, "release_year": 2022, "description": "顶级消费级CPU，适合AI开发"},
{"id": "ryzen97950x3d", "name": "AMD Ryzen 9 7950X3D", "manufacturer": "AMD", "architecture": "Zen 4", "cores": 16, "threads": 32, "base_clock_ghz": 4.2, "boost_clock_ghz": 5.7, "l3_cache_mb": 144, "tdp_watts": 120, "price_usd": 700, "release_year": 2023, "description": "带3D V-Cache，游戏性能更强"},
{"id": "intel14900k", "name": "Intel Core i9-14900K", "manufacturer": "Intel", "architecture": "Raptor Lake Refresh", "cores": 24, "threads": 32, "base_clock_ghz": 3.2, "boost_clock_ghz": 6.0, "l3_cache_mb": 36, "tdp_watts": 125, "price_usd": 580, "release_year": 2023, "description": "Intel顶级消费级CPU"}
]

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[
{"id": "h100", "name": "NVIDIA H100", "manufacturer": "NVIDIA", "architecture": "Hopper", "cuda_cores": 16896, "tensor_cores": 528, "memory_gb": 80, "memory_bandwidth_gbs": 3352, "fp32_tflops": 67, "fp16_tflops": 1979, "int8_perf_tops": 3958, "price_usd": 30000, "release_year": 2022, "description": "数据中心顶级GPU，专为AI训练设计"},
{"id": "a100", "name": "NVIDIA A100", "manufacturer": "NVIDIA", "architecture": "Ampere", "cuda_cores": 6912, "tensor_cores": 432, "memory_gb": 80, "memory_bandwidth_gbs": 2039, "fp32_tflops": 19.5, "fp16_tflops": 312, "int8_perf_tops": 624, "price_usd": 10000, "release_year": 2020, "description": "数据中心主力GPU，AI训练推理通用"},
{"id": "a10040g", "name": "NVIDIA A100 40GB", "manufacturer": "NVIDIA", "architecture": "Ampere", "cuda_cores": 6912, "tensor_cores": 432, "memory_gb": 40, "memory_bandwidth_gbs": 1555, "fp32_tflops": 19.5, "fp16_tflops": 312, "int8_perf_tops": 624, "price_usd": 6000, "release_year": 2020, "description": "A100 40GB版本，性价比更高"},
{"id": "l40s", "name": "NVIDIA L40S", "manufacturer": "NVIDIA", "architecture": "Ada Lovelace", "cuda_cores": 18176, "tensor_cores": 568, "memory_gb": 48, "memory_bandwidth_gbs": 864, "fp32_tflops": 91.6, "fp16_tflops": 362, "int8_perf_tops": 724, "price_usd": 7000, "release_year": 2023, "description": "新一代数据中心GPU，推理优化"},
{"id": "rtx4090", "name": "NVIDIA RTX 4090", "manufacturer": "NVIDIA", "architecture": "Ada Lovelace", "cuda_cores": 16384, "tensor_cores": 512, "memory_gb": 24, "memory_bandwidth_gbs": 1008, "fp32_tflops": 82.6, "fp16_tflops": 330, "int8_perf_tops": 660, "price_usd": 1600, "release_year": 2022, "description": "消费级最强GPU，适合个人AI开发"},
{"id": "rtx4090d", "name": "NVIDIA RTX 4090D", "manufacturer": "NVIDIA", "architecture": "Ada Lovelace", "cuda_cores": 14592, "tensor_cores": 456, "memory_gb": 24, "memory_bandwidth_gbs": 1008, "fp32_tflops": 73.5, "fp16_tflops": 294, "int8_perf_tops": 588, "price_usd": 1400, "release_year": 2024, "description": "4090中国特供版，性能略降"},
{"id": "rtx3090", "name": "NVIDIA RTX 3090", "manufacturer": "NVIDIA", "architecture": "Ampere", "cuda_cores": 10496, "tensor_cores": 328, "memory_gb": 24, "memory_bandwidth_gbs": 936, "fp32_tflops": 35.6, "fp16_tflops": 142, "int8_perf_tops": 284, "price_usd": 1200, "release_year": 2020, "description": "上一代旗舰，性价比高"},
{"id": "rtx3080", "name": "NVIDIA RTX 3080", "manufacturer": "NVIDIA", "architecture": "Ampere", "cuda_cores": 8704, "tensor_cores": 272, "memory_gb": 10, "memory_bandwidth_gbs": 760, "fp32_tflops": 29.8, "fp16_tflops": 119, "int8_perf_tops": 238, "price_usd": 700, "release_year": 2020, "description": "中高端消费级GPU"},
{"id": "v100", "name": "NVIDIA V100", "manufacturer": "NVIDIA", "architecture": "Volta", "cuda_cores": 5120, "tensor_cores": 640, "memory_gb": 32, "memory_bandwidth_gbs": 900, "fp32_tflops": 14.8, "fp16_tflops": 118, "int8_perf_tops": 236, "price_usd": 4000, "release_year": 2017, "description": "上一代数据中心GPU，仍有价值"},
{"id": "mi300x", "name": "AMD MI300X", "manufacturer": "AMD", "architecture": "CDNA 3", "cuda_cores": 0, "tensor_cores": 304, "memory_gb": 192, "memory_bandwidth_gbs": 5300, "fp32_tflops": 81.7, "fp16_tflops": 1307, "int8_perf_tops": 2614, "price_usd": 15000, "release_year": 2023, "description": "AMD最强AI GPU，192GB显存"}
]

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[
{"id": "gpt4", "name": "GPT-4", "organization": "OpenAI", "parameters": 1760, "architecture": "Transformer", "context_length": 8192, "input_price": 0.03, "output_price": 0.06, "mmlu": 86.4, "humaneval": 67.0, "is_open_source": false, "license": "Proprietary", "description": "OpenAI最强大的多模态大模型", "created_at": "2024-01-01"},
{"id": "gpt4turbo", "name": "GPT-4 Turbo", "organization": "OpenAI", "parameters": 1760, "architecture": "Transformer", "context_length": 128000, "input_price": 0.01, "output_price": 0.03, "mmlu": 86.4, "humaneval": 67.0, "is_open_source": false, "license": "Proprietary", "description": "GPT-4增强版，128K上下文", "created_at": "2024-01-01"},
{"id": "gpt35", "name": "GPT-3.5 Turbo", "organization": "OpenAI", "parameters": 175, "architecture": "Transformer", "context_length": 16385, "input_price": 0.0005, "output_price": 0.0015, "mmlu": 70.0, "humaneval": 48.1, "is_open_source": false, "license": "Proprietary", "description": "性价比高的通用模型", "created_at": "2024-01-01"},
{"id": "claude3opus", "name": "Claude 3 Opus", "organization": "Anthropic", "parameters": 400, "architecture": "Transformer", "context_length": 200000, "input_price": 0.015, "output_price": 0.075, "mmlu": 86.8, "humaneval": 84.9, "is_open_source": false, "license": "Proprietary", "description": "Anthropic最强模型，200K上下文", "created_at": "2024-01-01"},
{"id": "claude3sonnet", "name": "Claude 3 Sonnet", "organization": "Anthropic", "parameters": 175, "architecture": "Transformer", "context_length": 200000, "input_price": 0.003, "output_price": 0.015, "mmlu": 79.0, "humaneval": 73.0, "is_open_source": false, "license": "Proprietary", "description": "平衡性能与成本", "created_at": "2024-01-01"},
{"id": "llama270b", "name": "Llama 2 70B", "organization": "Meta", "parameters": 70, "architecture": "Transformer", "context_length": 4096, "input_price": 0, "output_price": 0, "mmlu": 69.8, "humaneval": 29.9, "is_open_source": true, "license": "Llama 2 Community", "description": "Meta开源大模型，70B参数", "created_at": "2024-01-01"},
{"id": "llama3", "name": "Llama 3 70B", "organization": "Meta", "parameters": 70, "architecture": "Transformer", "context_length": 8192, "input_price": 0, "output_price": 0, "mmlu": 82.0, "humaneval": 81.7, "is_open_source": true, "license": "Llama 3 Community", "description": "Meta最新开源模型，性能接近GPT-4", "created_at": "2024-01-01"},
{"id": "mistral7b", "name": "Mistral 7B", "organization": "Mistral AI", "parameters": 7, "architecture": "Transformer", "context_length": 32768, "input_price": 0, "output_price": 0, "mmlu": 62.5, "humaneval": 26.8, "is_open_source": true, "license": "Apache 2.0", "description": "小巧高效的开源模型", "created_at": "2024-01-01"},
{"id": "mixtral8x7b", "name": "Mixtral 8x7B", "organization": "Mistral AI", "parameters": 47, "architecture": "MoE", "context_length": 32768, "input_price": 0, "output_price": 0, "mmlu": 70.6, "humaneval": 40.2, "is_open_source": true, "license": "Apache 2.0", "description": "MoE架构，高效推理", "created_at": "2024-01-01"},
{"id": "qwen72b", "name": "Qwen 72B", "organization": "Alibaba", "parameters": 72, "architecture": "Transformer", "context_length": 32768, "input_price": 0, "output_price": 0, "mmlu": 83.1, "humaneval": 65.4, "is_open_source": true, "license": "Apache 2.0", "description": "阿里开源大模型，中文能力强", "created_at": "2024-01-01"},
{"id": "deepseekv3", "name": "DeepSeek V3", "organization": "DeepSeek", "parameters": 685, "architecture": "MoE", "context_length": 128000, "input_price": 0.00014, "output_price": 0.00028, "mmlu": 88.5, "humaneval": 86.2, "is_open_source": true, "license": "MIT", "description": "DeepSeek最新模型，性价比极高", "created_at": "2024-01-01"},
{"id": "glm4", "name": "GLM-4", "organization": "Zhipu AI", "parameters": 130, "architecture": "Transformer", "context_length": 128000, "input_price": 0.014, "output_price": 0.014, "mmlu": 81.0, "humaneval": 70.0, "is_open_source": false, "license": "Proprietary", "description": "智谱AI大模型，中文能力强", "created_at": "2024-01-01"}
]