Compare DeepSeek V4 Flash from DeepSeek and Kimi K2 0711 from Moonshot AI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
DeepSeek V4 Flash
Kimi K2 0711(This model currently points to the older 0423 version; if you need to request the latest version, you can choose the model deepseek-v4-flash-0731)DeepSeek-V4 features an ultra-long context of one million characters and achieves leading performance domestically and in the open-source domain in agent capabilities, world knowledge, and reasoning.
Kimi-K2 is a MoE architecture foundational model with extremely powerful coding and agent capabilities, featuring a total of 1 trillion parameters and activating 32 billion parameters. In benchmark performance tests across major categories such as general knowledge reasoning, programming, mathematics, and agents, the K2 model outperforms other mainstream open-source models. The Kimi-K2 model supports a context length of 128k tokens. It does not support visual capabilities.
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.
DeepSeek V4 Flash: $0.284/M output tokens; Kimi K2 0711: $2.16/M. Use the cost calculator above to estimate your own workload.
DeepSeek V4 Flash: 1483; Kimi K2 0711: 1467 (LMArena coding leaderboard).
Kimi K2 0711: 0.8s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
DeepSeek V4 Flash accepts 1,000,000 and Kimi K2 0711 accepts 131,072 input tokens. Maximum output per request is 384,000 tokens on DeepSeek V4 Flash and 16,384 tokens on Kimi K2 0711.
DeepSeek V4 Flash at 66.5 tok/s and Kimi K2 0711 at 50.2 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
DeepSeek V4 Flash accepts text input and supports tool calling, function calling, structured outputs and thinking; Kimi K2 0711 accepts text input and supports tool calling, function calling and structured outputs.
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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