Compare Kimi K2 0905 from Moonshot AI and DeepSeek V4 Flash from DeepSeek on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
Kimi K2 0905
DeepSeek V4 FlashKimi-K2-0905 is a large-scale Mixture of Experts (MoE) language model developed by Moonshot AI, with a total of 1 trillion parameters and 32 billion active parameters per forward pass. It supports long-context inference of up to 256k tokens, an expansion from the previous 128k.
DeepSeek V4 Flash 0423 is DeepSeek's efficiency-optimized Mixture-of-Experts text model, designed for fast inference and workflows requiring tool use, function calling, and structured outputs. It features 284B total parameters with 13B activated parameters and supports a 1M-token context window with cost-effective pricing.
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.
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: $0.928/M output tokens; Kimi K2 0905: $2.192/M. Use the cost calculator above to estimate your own workload.
Kimi K2 0905: 0.1s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
DeepSeek V4 Flash at 59.0 tok/s and Kimi K2 0905 at 49.0 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
Kimi K2 0905 accepts text input and supports tool calling, function calling and structured outputs; DeepSeek V4 Flash 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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