Anthropic的Claude模型提供先进的安全AI能力,专注于有用、无害、诚实的AI助手体验,并具备强大的推理和对话能力。
| 模型名称 | Input Token Range | 上下文 | 输入(/Mt) | 缓存写入(/Mt) | 缓存读取(/Mt) | 输出(/Mt) | 操作 |
|---|---|---|---|---|---|---|---|
| claude-fable-5官方资源 | - | 1,000,000 | $10 | $12.5(5m)·$20(1h) | $1 | $50 | |
| claude-opus-4-7官方资源 | - | 1,000,000 | $4.75$5 | $5.9375(5m)·$9.5(1h)$6.25(5m)·$10(1h) | $0.475$0.5 | $23.75$25 | |
| claude-opus-5官方资源 | - | 1,000,000 | $5 | $6.25(5m)·$10(1h) | $0.5 | $25 | |
| claude-sonnet-5官方资源 | - | 1,000,000 | $2 | $2.5(5m)·$4(1h) | $0.2 | $10 | |
| claude-opus-4-8官方资源 | - | 1,000,000 | $4.75$5 | $5.9375(5m)·$9.5(1h)$6.25(5m)·$10(1h) | $0.475$0.5 | $23.75$25 | |
| claude-opus-4-8-r低价专区 | - | 1,000,000 | $1$5 | $1.25(5m)·$2(1h)$6.25(5m)·$10(1h) | $0.1$0.5 | $5$25 | |
| claude-opus-4-7-r低价专区 | - | 1,000,000 | $1$5 | $1.25(5m)·$2(1h)$6.25(5m)·$10(1h) | $0.1$0.5 | $5$25 | |
| claude-opus-4-6-dd低价专区 | - | 1,000,000 | $2.75$5 | $3.4375(5m)·$5.5(1h)$6.25(5m)·$10(1h) | $0.275$0.5 | $13.75$25 | |
| claude-opus-4-6官方资源 | 1-200,000 | 1,000,000 | $5 | $6.25(5m)·$10(1h) | $0.5 | $25 | |
| 200,000-1,000,000 | 1,000,000 | $5 | $6.25(5m)·$10(1h) | $0.5 | $25 | ||
| claude-opus-4-6-r低价专区 | - | 1,000,000 | $1$5 | $1.25(5m)·$2(1h)$6.25(5m)·$10(1h) | $0.1$0.5 | $5$25 | |
| claude-sonnet-4-6官方资源 | 1-200,000 | 1,000,000 | $3 | $3.75(5m)·$6(1h) | $0.3 | $15 | |
| 200,000-1,000,000 | 1,000,000 | $3 | $3.75(5m)·$6(1h) | $0.3 | $15 | ||
| claude-sonnet-4-6-dd低价专区 | - | 1,000,000 | $1.65$3 | $2.0625(5m)·$3.3(1h)$3.75(5m)·$6(1h) | $0.165$0.3 | $8.25$15 | |
| claude-sonnet-4-6-r低价专区 | - | 1,000,000 | $0.6$3 | $0.75(5m)·$1.2(1h)$3.75(5m)·$6(1h) | $0.06$0.3 | $3$15 | |
| claude-opus-4-5-20251101官方资源 | - | 200,000 | $4.75$5 | $5.9375(5m)·$9.5(1h)$6.25(5m)·$10(1h) | $0.475$0.5 | $23.75$25 | |
| claude-opus-4-5-20251101-dd低价专区 | - | 200,000 | $2.75$5 | $3.4375(5m)$6.25(5m) | $0.275$0.5 | $13.75$25 | |
| claude-sonnet-4-5-20250929官方资源 | 1-200,000 | 200,000 | $3 | $3.75(5m)·$6(1h) | $0.3 | $15 | |
| 200,000-1,000,000 | 200,000 | $6 | $7.5(5m)·$12(1h) | $0.6 | $22.5 | ||
| claude-sonnet-4-5-20250929-dd低价专区 | - | 200,000 | $1.65$3 | $2.0625(5m)$3.75(5m) | $0.165$0.3 | $8.25$15 | |
| claude-haiku-4-5-20251001官方资源 | - | 20,000 | $1 | $1.25(5m)·$2(1h) | $0.1 | $5 | |
| claude-haiku-4-5-20251001-dd低价专区 | - | 200,000 | $0.55$1 | $0.6875(5m)·$1.1(1h)$1.25(5m)·$2(1h) | $0.055$0.1 | $2.75$5 | |
| claude-haiku-4-5-20251001-r低价专区 | - | 200,000 | $0.2$1 | $0.25(5m)·$0.4(1h)$1.25(5m)·$2(1h) | $0.02$0.1 | $1$5 | |
| claude-opus-4-8-cc低价专区 | - | 1,000,000 | $1.85$5 | $2.3125(5m)·$3.7(1h)$6.25(5m)·$10(1h) | $0.185$0.5 | $9.25$25 | |
| claude-opus-4-6-cc低价专区 | - | 1,000,000 | $1.85$5 | $2.3125(5m)·$3.7(1h)$6.25(5m)·$10(1h) | $0.185$0.5 | $9.25$25 | |
| claude-opus-4-7-cc低价专区 | - | 1,000,000 | $1.85$5 | $2.3125(5m)·$3.7(1h)$6.25(5m)·$10(1h) | $0.185$0.5 | $9.25$25 | |
| claude-sonnet-4-6-cc低价专区 | - | 1,000,000 | $1.11$3 | $1.3875(5m)·$2.22(1h)$3.75(5m)·$6(1h) | $0.111$0.3 | $5.55$15 | |
| claude-haiku-4-5-20251001-cc低价专区 | - | 200,000 | $0.37$1 | $0.4625(5m)·$0.74(1h)$1.25(5m)·$2(1h) | $0.037$0.1 | $1.85$5 |
OpenAI的GPT系列模型提供最先进的语言理解和生成能力,在多种任务中表现出色,是业界领先的AI模型。
| 模型名称 | Input Token Range | 上下文 | 输入(/Mt) | 缓存写入(/Mt) | 缓存读取(/Mt) | 输出(/Mt) | 操作 |
|---|---|---|---|---|---|---|---|
| gpt-5.6-terra-es低价专区 | 1-272,000 | 3,720,000 | $0.25$2.5 | $0.3125(30m)$3.125(30m) | $0.025$0.25 | $1.5$15 | |
| 272,000-372,000 | 3,720,000 | $0.5$5 | $0.625(30m)$6.25(30m) | $0.05$0.5 | $2.25$22.5 | ||
| gpt-5.6-luna-es低价专区 | 1-272,000 | 372,000 | $0.1$1 | $0.125(30m)$1.25(30m) | $0.01$0.1 | $0.6$6 | |
| 272,000-372,000 | 372,000 | $0.2$2 | $0.25(30m)$2.5(30m) | $0.02$0.2 | $0.9$9 | ||
| gpt-5.6-sol-es低价专区 | 1-272,000 | 372,000 | $0.5$5 | $0.625(30m)$6.25(30m) | $0.05$0.5 | $3$30 | |
| 272,000-372,000 | 372,000 | $1$10 | $1.25(30m)$12.5(30m) | $0.1$1 | $4.5$45 | ||
| gpt-5.6-terra官方资源 | 1-272,000 | 1,050,000 | $2.5 | $3.125(30m) | $0.25 | $15 | |
| 272,000-1,050,000 | 1,050,000 | $5 | $6.25(30m) | $0.5 | $22.5 | ||
| gpt-5.6-luna官方资源 | 1-272,000 | 1,050,000 | $1 | $1.25(30m) | $0.1 | $6 | |
| 272,000-1,050,000 | 1,050,000 | $2 | $2.5(30m) | $0.2 | $9 | ||
| gpt-5.6-sol官方资源 | 1-272,000 | 1,050,000 | $5 | $6.25(30m) | $0.5 | $30 | |
| 272,000-1,050,000 | 1,050,000 | $10 | $12.5(30m) | $1 | $45 | ||
| gpt-5.5-r低价专区 | - | 1,050,000 | $0.5$5 | - | $0.05$0.5 | $3$30 | |
| gpt-5.5官方资源 | 1-272,000 | 1,050,000 | $4.75$5 | - | $0.475$0.5 | $28.5$30 | |
| 272,000-1,050,000 | 1,050,000 | $9.5$10 | - | $0.95$1 | $42.75$45 | ||
| gpt-4.1-nano官方资源 | - | 1,047,576 | $0.095$0.1 | - | $0.0237$0.025 | $0.38$0.4 | |
| gpt-5.5-pro官方资源 | 1-272,000 | 1,050,000 | $30 | - | - | $180 | |
| 272,000-1,050,000 | 1,050,000 | $60 | - | - | $270 | ||
| gpt-5.4-pro官方资源 | 1-272,000 | 1,050,000 | $30 | - | - | $180 | |
| 272,000-1,050,000 | 1,050,000 | $60 | - | - | $270 | ||
| gpt-5.4官方资源 | 1-272,000 | 1,050,000 | $2.5 | - | $0.25 | $15 | |
| 272,000-1,050,000 | 1,050,000 | $5 | - | $0.5 | $22.5 | ||
| gpt-5.4-mini官方资源 | - | 400,000 | $0.7125$0.75 | - | $0.0712$0.075 | $4.275$4.5 | |
| gpt-5.4-nano官方资源 | - | 400,000 | $0.19$0.2 | - | $0.019$0.02 | $1.1875$1.25 | |
| gpt-5.3-codex官方资源 | - | 400,000 | $1.6625$1.75 | - | $0.1662$0.175 | $13.3$14 | |
| gpt-5.2-pro官方资源 | - | 400,000 | $19.95$21 | - | - | $159.6$168 | |
| gpt-5.2-codex官方资源 | - | 400,000 | $1.75 | - | $0.175 | $14 | |
| gpt-5.2官方资源 | - | 400,000 | $1.6625$1.75 | - | $0.1662$0.175 | $13.3$14 | |
| gpt-5.1-codex-max官方资源 | - | 400,000 | $1.1875$1.25 | - | $0.1187$0.125 | $9.5$10 | |
| gpt-5.1-codex官方资源 | - | 400,000 | $1.1875$1.25 | - | $0.1187$0.125 | $9.5$10 | |
| gpt-5.1-codex-mini官方资源 | - | 400,000 | $0.2375$0.25 | - | $0.0237$0.025 | $1.9$2 | |
| gpt-5.1官方资源 | - | 400,000 | $1.1875$1.25 | - | $0.1187$0.125 | $9.5$10 | |
| gpt-5-pro官方资源 | - | 400,000 | $14.25$15 | - | - | $114$120 | |
| gpt-5-codex官方资源 | - | 400,000 | $1.1875$1.25 | - | $0.1187$0.125 | $9.5$10 | |
| gpt-5官方资源 | - | 400,000 | $1.1875$1.25 | - | $0.1187$0.125 | $9.5$10 | |
| gpt-5-mini官方资源 | - | 400,000 | $0.2375$0.25 | - | $0.0237$0.025 | $1.9$2 | |
| gpt-5-nano官方资源 | - | 400,000 | $0.0475$0.05 | - | $0.0047$0.005 | $0.38$0.4 | |
| gpt-4.1官方资源 | - | 1,047,576 | $2 | - | $0.5 | $8 | |
| gpt-4.1-mini官方资源 | - | 1,047,576 | $0.4 | - | $0.1 | $1.6 | |
| gpt-4o官方资源 | - | 131,072 | $2.375$2.5 | - | $1.1875$1.25 | $9.5$10 | |
| gpt-4o-mini官方资源 | - | 128,000 | $0.1425$0.15 | - | $0.0712$0.075 | $0.57$0.6 | |
| OpenAI: GPT OSS 20B | - | 131,072 | $0.05 | - | - | $0.2 | |
| OpenAI GPT OSS 120B | - | 131,072 | $0.1 | - | - | $0.5 |
Google的Gemini模型提供高质量的语言处理能力,在各种NLP任务中表现出色,并具备强大的多模态能力。
| 模型名称 | Input Token Range | 上下文 | 输入(/Mt) | 缓存写入(/Mt) | 缓存读取(/Mt) | 输出(/Mt) | 操作 |
|---|---|---|---|---|---|---|---|
| gemini-3.1-flash-lite | - | 1,048,576 | $0.25 | $0.083(5m)·$1(1h) | $0.025 | $1.5 | |
| gemini-3.5-flash官方资源 | - | 1,048,576 | $1.425$1.5 | $0.0788(5m)·$0.95(1h)$0.083(5m)·$1(1h) | $0.1425$0.15 | $8.55$9 | |
| gemini-3.1-pro-preview官方资源 | 1-204,800 | 1,048,576 | $2 | $0.375(5m)·$4.5(1h) | $0.2 | $12 | |
| 204,800-1,048,576 | 1,048,576 | $4 | $0.375(5m)·$4.5(1h) | $0.4 | $18 | ||
| gemini-3-flash-preview官方资源 | - | 1,048,576 | $0.475$0.5 | $0.0788(5m)·$0.95(1h)$0.083(5m)·$1(1h) | $0.0475$0.05 | $2.85$3 | |
| gemini-2.5-pro官方资源 | - | 1,048,576 | $1.1875$1.25 | $0.3562(5m)·$4.275(1h)$0.375(5m)·$4.5(1h) | $0.1187$0.125 | $9.5$10 | |
| gemini-2.5-pro-preview-06-05官方资源 | - | 1,048,576 | $1.1875$1.25 | $0.3562(5m)·$4.275(1h)$0.375(5m)·$4.5(1h) | $0.1187$0.125 | $9.5$10 | |
| gemini-2.5-flash-preview-05-20官方资源 | - | 1,048,576 | $0.1425$0.15 | $0.0788(5m)·$0.95(1h)$0.083(5m)·$1(1h) | $0.0285$0.03 | $3.325$3.5 | |
| gemini-2.5-flash | - | 1,048,576 | $0.285$0.3 | $0.0788(5m)·$0.95(1h)$0.083(5m)·$1(1h) | $0.0285$0.03 | $2.375$2.5 | |
| gemini-2.5-flash-lite-preview-09-2025官方资源 | - | 1,048,576 | $0.095$0.1 | $0.0788(5m)·$0.95(1h)$0.083(5m)·$1(1h) | $0.0095$0.01 | $0.38$0.4 | |
| gemini-2.5-flash-lite官方资源 | - | 1,048,576 | $0.095$0.1 | $0.0788(5m)·$0.95(1h)$0.083(5m)·$1(1h) | $0.0095$0.01 | $0.38$0.4 | |
| Gemma 3 27B | - | 32,768 | $0.119 | - | - | $0.2 | |
| Gemma3 12B | - | 131,072 | $0.05 | - | - | $0.1 | |
| gemini-3.6-flash官方资源 | - | 1,048,576 | $1.5 | $0.0833(5m)·$1(1h) | $0.15 | $7.5 | |
| gemini-3.5-flash-lite官方资源 | - | 1,048,576 | $0.3 | $0.0833(5m)·$1(1h) | $0.03 | $2.5 |
Qwen系列模型提供高效的语言处理能力,具有多种参数规模,涵盖从轻量级到企业级的解决方案。
| 模型名称 | Input Token Range | 上下文 | 输入(/Mt) | 缓存读取(/Mt) | 输出(/Mt) | 操作 |
|---|---|---|---|---|---|---|
| Qwen3.5-Plus | 1-256,000 | 1,000,000 | $0.4 | - | $2.4 | |
| 256,000-1,000,000 | 1,000,000 | $1.2 | - | $7.2 | ||
| Qwen3 235B A22B Instruct 2507 | - | 131,072 | $0.15 | - | $0.8 | |
| Qwen 2.5 72B Instruct | - | 32,000 | $0.38 | - | $0.4 | |
| Qwen MT Plus | - | 4,096 | $0.25 | - | $0.75 | |
| Qwen2.5 7B Instruct | - | 32,000 | $0.07 | - | $0.07 | |
| Qwen2.5 VL 72B Instruct | - | 32,768 | $0.8 | - | $0.8 | |
| Qwen3 30B A3B | - | 40,960 | $0.09 | - | $0.45 | |
| Qwen3 32B | - | 40,960 | $0.1 | - | $0.45 | |
| Qwen3 235B A22B | - | 40,960 | $0.2 | - | $0.8 | |
| Qwen3 235B A22b Thinking 2507 | - | 131,072 | $0.3 | - | $3 | |
| Qwen3 Coder 480B A35B Instruct | - | 262,144 | $0.29 | - | $1.2 | |
| Qwen3 Coder Next FP8 | - | 262,144 | $0.2 | - | $1.5 | |
| Qwen3 Next 80B A3B Instruct | - | 65,536 | $0.15 | - | $1.5 | |
| Qwen3 Next 80B A3B Thinking | - | 65,536 | $0.15 | - | $1.5 | |
| Qwen3.5-27B | - | 262,144 | $0.3 | - | $2.4 | |
| Qwen3.8 Max | - | 1,000,000 | $2 | $0.25 | $6 | |
| Qwen3.5-122B-A10B | - | 262,144 | $0.4 | - | $3.2 | |
| Qwen3.5-35B-A3B | - | 262,144 | $0.25 | - | $2 | |
| Qwen3.5-397B-A17B | - | 262,144 | $0.6 | - | $3.6 |
来自清华大学的GLM系列模型,具备先进的中文语言理解和生成能力。
| 模型名称 | 上下文 | 输入(/Mt) | 缓存读取(/Mt) | 输出(/Mt) | 操作 |
|---|---|---|---|---|---|
| GLM 5.2 | 1,048,576 | $1.4 | $0.26 | $4.4 | |
| GLM-5.1 | 204,800 | $1.38 | $0.26 | $4.4 | |
| GLM-5V-Turbo | 204,800 | $1.2 | $0.24 | $4 | |
| GLM 4.5V | 65,536 | $0.6 | - | $1.8 | |
| GLM-4.5 | 131,072 | $0.6 | - | $2.2 | |
| GLM-4.7 | 204,800 | $0.6 | - | $2.2 | |
| GLM-4.7-Flash | 200,000 | $0.07 | $0.01 | $0.4 | |
| GLM-5 | 204,800 | $1 | $0.2 | $3.2 | |
| GLM-5-Turbo | 202,800 | $1.2 | $0.24 | $4 |
来自DeepSeek的先进AI模型,为企业级和研究应用提供前沿的推理能力和具有竞争力的价格。
| 模型名称 | 上下文 | 输入(/Mt) | 缓存写入(/Mt) | 缓存读取(/Mt) | 输出(/Mt) | 操作 |
|---|---|---|---|---|---|---|
| Deepseek V4 Flash 0731 | 1,048,576 | $0.14 | - | $0.028 | $0.28 | |
| Deepseek V4 Flash | 1,048,576 | $0.14 | - | $0.028 | $0.28 | |
| Deepseek V4 Pro | 1,048,576 | $0.435 | - | $0.145 | $0.87 | |
| DeepSeek R1 0528 | 163,840 | $0.7 | - | $0.35 | $2.5 | |
| DeepSeek V3 0324 | 163,840 | $0.28 | $0.14(5m) | $0.14 | $1.14 | |
| DeepSeek V3.1 | 163,840 | $0.27 | - | - | $1 | |
| DeepSeek-OCR 2 | 8,192 | $0.03 | - | - | $0.03 |
最先进AI模型的高级集合,具备高级推理、数学证明能力以及跨多个领域的前沿语言理解能力。
| 模型名称 | Input Token Range | 上下文 | 输入(/Mt) | 缓存写入(/Mt) | 缓存读取(/Mt) | 输出(/Mt) | 操作 |
|---|---|---|---|---|---|---|---|
| Qwen3.5-Plus | 1-256,000 | 1,000,000 | $0.4 | - | - | $2.4 | |
| 256,000-1,000,000 | 1,000,000 | $1.2 | - | - | $7.2 | ||
| Deepseek V4 Flash 0731 | - | 1,048,576 | $0.14 | - | $0.028 | $0.28 | |
| GLM 5.2 | - | 1,048,576 | $1.4 | - | $0.26 | $4.4 | |
| Deepseek V4 Flash | - | 1,048,576 | $0.14 | - | $0.028 | $0.28 | |
| Deepseek V4 Pro | - | 1,048,576 | $0.435 | - | $0.145 | $0.87 | |
| MiniMax M2.7 | - | 204,800 | $0.3 | - | $0.03 | $1.2 | |
| Kimi K2.5 | - | 262,144 | $0.6 | - | $0.1 | $3 | |
| Kimi K2 Instruct | - | 131,072 | $0.57 | - | - | $2.3 | |
| GLM-5.1 | - | 204,800 | $1.38 | - | $0.26 | $4.4 | |
| GLM-5V-Turbo | - | 204,800 | $1.2 | - | $0.24 | $4 | |
| ERNIE 4.5 VL 424B A47B | - | 123,000 | $0.42 | - | - | $1.25 | |
| OpenAI: GPT OSS 20B | - | 131,072 | $0.05 | - | - | $0.2 | |
| OpenAI GPT OSS 120B | - | 131,072 | $0.1 | - | - | $0.5 | |
| DeepSeek R1 0528 | - | 163,840 | $0.7 | - | $0.35 | $2.5 | |
| DeepSeek V3 0324 | - | 163,840 | $0.28 | $0.14(5m) | $0.14 | $1.14 | |
| DeepSeek V3.1 | - | 163,840 | $0.27 | - | - | $1 | |
| ERNIE 4.5 300B A47B | - | 123,000 | $0.28 | - | - | $1.1 | |
| GLM 4.5V | - | 65,536 | $0.6 | - | - | $1.8 | |
| GLM-4.5 | - | 131,072 | $0.6 | - | - | $2.2 | |
| GLM-4.7 | - | 204,800 | $0.6 | - | - | $2.2 | |
| GLM-4.7-Flash | - | 200,000 | $0.07 | - | $0.01 | $0.4 | |
| GLM-5 | - | 204,800 | $1 | - | $0.2 | $3.2 | |
| GLM-5-Turbo | - | 202,800 | $1.2 | - | $0.24 | $4 | |
| Llama 4 Maverick Instruct | - | 1,048,576 | $0.17 | - | - | $0.85 | |
| Llama 4 Scout Instruct | - | 131,072 | $0.1 | - | - | $0.5 | |
| MiniMax M1 | - | 1,000,000 | $0.55 | - | - | $2.2 | |
| Minimax M2.1 | - | 204,800 | $0.3 | $0.375(5m) | $0.03 | $1.2 | |
| MiniMax M2.5 | - | 204,800 | $0.3 | - | $0.03 | $1.2 | |
| MiniMax M2.7-highspeed | - | 204,800 | $0.6 | - | $0.06 | $2.4 | |
| MiniMax M2.5-highspeed | - | 204,800 | $0.6 | - | $0.03 | $2.4 | |
| Qwen3 30B A3B | - | 40,960 | $0.09 | - | - | $0.45 | |
| Qwen3 32B | - | 40,960 | $0.1 | - | - | $0.45 | |
| Qwen3 235B A22B | - | 40,960 | $0.2 | - | - | $0.8 | |
| Qwen3 235B A22b Thinking 2507 | - | 131,072 | $0.3 | - | - | $3 | |
| Qwen3.8 Max | - | 1,000,000 | $2 | - | $0.25 | $6 | |
| XiaomiMiMo/MiMo-V2.5-Pro | 1-262,144 | 1,048,576 | $1 | - | $0.2 | $3 | |
| 262,144-1,048,576 | 1,048,576 | $2 | - | $0.4 | $6 | ||
| Qwen3.5-122B-A10B | - | 262,144 | $0.4 | - | - | $3.2 | |
| Qwen3.5-35B-A3B | - | 262,144 | $0.25 | - | - | $2 | |
| Qwen3.5-397B-A17B | - | 262,144 | $0.6 | - | - | $3.6 |