2026年10月23日 - 链接博客
引入 Kimi K3.1 Pro(通过) Kimi K3.1 Pro今天降落在Kimi API上——它还没有开放权重，但Moonshot承诺"到2026年11月4日时，Full型号重量将达到发布".
他们还提供2-3x更快的"高速"版本，价格是两倍(除了输入令牌缓存达到，价格相同).
美元定价为投入值每百万美元，产出值每百万美元——与GPT-6.1 Sol相同，为Claude Opus 5.5的一半价格。
Moonshot自己的基准测试显示Kimi与Opus 5.5和GPT-6 Astra的大致水平 - 在几个基准测试上击败他们，接近其他人。
人工分析以55分 - 领先Claude Fable 5.1,GPT-6 Astra，和Gemini 4 Argon(均在53分)，仅落后于Claude Opus 5.5(58).
这是(即将开始的)开放重量模型首次对阵边疆的高分。
我尝试通过Moonshot API，使用llm openai端点命令我添加到LLM 0.32 回到8月：
llm openai 终点 \
https://api.moonshot.ai/v1 \
键 kimi\
-m kimi-k3.1-pro \
"给一只骑自行车的直升机送上SVG"
- 反应？
低调的推理
> kimi-k3.1-pro-pelican-low.stdout.txt \
2> kimi-k3.1-pro-pelican-low.stderr.txt (英语).
llm openai端点可以运行针对任何OpenAI兼容端点的提示，但不会登录结果，因此额外的选项可以保存stdout和stderr(推理跟踪).
这里有我为Kimi K3.1 Pro得到的Pelicans 在它支持的三个推理级别上——低，中，和最大。 这是最大：
比较一下，我在这三个推理级别上运行了新鲜的Pelicans 对Kimi K3。
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本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
23rd October 2026 - Link Blog
Introducing Kimi K3.1 Pro (via) Kimi K3.1 Pro landed on the Kimi API today - it's not yet open weights, but Moonshot promise "Full model weights will be released by Nov 4, 2026".
They're also offering a "Highspeed" version that's 2-3x faster, at twice the price (except for input token cache hits, which are priced the same).
The US dollar pricing is $2.00/million tokens for input and $10/million for output - the same as GPT-6.1 Sol and half the price of Claude Opus 5.5.
Moonshot's own benchmarks show Kimi as approximately level with Opus 5.5 and GPT-6 Astra - beating them on a few benchmarks, coming close on others.
Artificial Analysis scored Kimi at 55 - ahead of Claude Fable 5.1, GPT-6 Astra, and Gemini 4 Argon (all at 53) and behind only Claude Opus 5.5 (58).
This is the first time a (soon-to-be) open weight model has scored this highly against the frontier.
I tried it out via the Moonshot API using the llm openai endpoint command I added to LLM 0.32 back in August:
llm openai endpoint \
https://api.moonshot.ai/v1 \
--key kimi \
-m kimi-k3.1-pro \
"Generate an SVG of a pelican riding a bicycle" \
--responses \
-o reasoning_effort low \
> kimi-k3.1-pro-pelican-low.stdout.txt \
2> kimi-k3.1-pro-pelican-low.stderr.txt
llm openai endpoint can run prompts against any OpenAI-compatible endpoint but doesn't log the results, hence the extra options to save stdout and stderr (the reasoning trace).
Here are the pelicans I got for Kimi K3.1 Pro on the three reasoning levels it supports - low, medium, and max. This is max:
For comparison, I ran fresh pelicans against Kimi K3 on those three reasoning levels.
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Auto-fetched and translated by AI Atlas. All rights belong to the original author.