Compare Kimi K3 from Moonshot AI and MiMo V2 Flash from Xiaomi on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
Kimi K3
MiMo V2 FlashKimi K3 is Kimi’s flagship model for long-horizon coding and end-to-end knowledge work, with a 1M-token context window and industry-leading intelligence.
MiMo-V2-Flash is a mixture of experts (MoE) language model with a total of 309 billion parameters and 15 billion activated parameters. It is designed for high-speed inference and proxy workflows, adopting a novel hybrid attention architecture and multi-token prediction (MTP), significantly reducing inference costs while achieving state-of-the-art performance.
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Daily traffic served through AIHubMix — how demand for each model is trending.
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.
Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
MiMo V2 Flash: $0.5754/M output tokens; Kimi K3: $13.5/M. Use the cost calculator above to estimate your own workload.
Kimi K3: 1531; MiMo V2 Flash: 1446 (LMArena coding leaderboard).
Kimi K3 accepts 1,048,576 and MiMo V2 Flash accepts 1,048,576 input tokens. Maximum output per request is 1,048,576 tokens on Kimi K3 and 131,072 tokens on MiMo V2 Flash.
Kimi K3 accepts text, image and video input and supports thinking, function calling and structured outputs; MiMo V2 Flash accepts text, image, video and audio input and supports web search.
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
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