Kimi K2 Thinking is the latest generation open-source reasoning model, designed for advanced multi-step thinking and dynamic tool invocation. It achieves state-of-the-art performance on benchmarks such as HLE and BrowseComp, demonstrating exceptional reasoning depth and stability. Built with native INT4 quantization and a 256k context window, Kimi K2 delivers high precision with significantly reduced inference latency and memory usage, supporting 200–300 consecutive tool calls for long-context reasoning, complex task planning, and intelligent agent applications.
Pricing
- Input Tokens: $0.548 /M tokens
- Output Tokens: $2.192 /M tokens
- Cache Read: $0 /M tokens
Input Modalities
- Text
Context length
- 262K tokens
Max output
- 262K tokens
Capabilities
- Thinking
- Streaming
- Tool calling
- Web search
- URL context
- Code interpreter
- Computer use
- File search
- Memory tool
- Structured outputs
- Citations
- Prompt caching
- Background mode
- Server-side sessions
Providers
Sophnet s-kimi-k2-thinking
Pricing$0.548$2.192
Context262K
Max output262K
Latency2.4S
Throughput13.3TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Siliconflow sf-kimi-k2-thinking
Pricing$0.548$2.192
Context256K
Max output256K
Latency1.6S
Throughput42.4TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Moonshot kimi-k2-thinking
Pricing$0.548$2.192
Cache$0
Context262K
Max output262K
Latency2.4S
Throughput17.6TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Performance for kimi-k2-thinking
Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).
Uptime
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Try this model
Python