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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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data/gpus.json Normal file
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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"}
]