deepseek-r1
DeepSeek
Open-source reasoning model with visible chain-of-thought, tuned for math, coding, and multi-step problem solving.
- 上下文
- 164K
- 输入 / 1M tokens
- $0.7
- 输出 / 1M tokens
- $2.5
- 缓存读 / 1M
- $0
- 缓存写 / 1M
- $0
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deepseek-v3
DeepSeek
Open-source general-purpose LLM with representative instruction-following and coding skills within the open-weights ecosystem, suited for chat, code assistance, and enterprise text workflows.
- 上下文
- 131K
- 输入 / 1M tokens
- $0.287
- 输出 / 1M tokens
- $1.147
- 缓存读 / 1M
- $0.057
- 缓存写 / 1M
- -
deepseek-v3.1
DeepSeek
Hybrid model that switches between thinking and non-thinking modes on a single endpoint, post-trained for tool use and code agent workflows.
- 上下文
- 164K
- 输入 / 1M tokens
- $0.574
- 输出 / 1M tokens
- $1.721
- 缓存读 / 1M
- $0.13
- 缓存写 / 1M
- $0
deepseek-v3.2
DeepSeek
Best value for code and math. Fraction of flagship cost.
- 上下文
- 164K
- 输入 / 1M tokens
- $0.287
- 输出 / 1M tokens
- $0.431
- 缓存读 / 1M
- $0.058
- 缓存写 / 1M
- $0.359
deepseek-v3.2-exp
DeepSeek
Experimental interim release focused on long-context efficiency, with optional reasoning mode and V3.1-level performance overall.
- 上下文
- 164K
- 输入 / 1M tokens
- $0.287
- 输出 / 1M tokens
- $0.43
- 缓存读 / 1M
- $0
- 缓存写 / 1M
- $0
deepseek-v4-flash
DeepSeek
Faster, lower-cost variant of DeepSeek V4, optimized for coding assistants, high-throughput chat, and latency-sensitive Agent workflows.
- 上下文
- 1M
- 输入 / 1M tokens
- $0.22
- 输出 / 1M tokens
- $0.66
- 缓存读 / 1M
- $0.007
- 缓存写 / 1M
- $0
deepseek-v4-pro
DeepSeek
DeepSeek V4 flagship with adjustable reasoning depth, built for full-codebase analysis, multi-step automation, and complex reasoning tasks.
- 上下文
- 1M
- 输入 / 1M tokens
- $0.66
- 输出 / 1M tokens
- $1.98
- 缓存读 / 1M
- $0.022
- 缓存写 / 1M
- $0
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