Compare DeepSeek V4 Flash from DeepSeek and Gemini 2.0 Flash Exp Search from Google 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
Gemini 2.0 Flash Exp Search(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.
The gemini-2.0-flash-exp model supports internet connectivity, but the official version requires additional request parameters to enable it. Aihubmix has integrated this by automatically calling the official API's online functionality when the model name is requested with the "search" parameter.
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: $0.284/M output tokens; Gemini 2.0 Flash Exp Search: $0.4/M. Use the cost calculator above to estimate your own workload.
DeepSeek V4 Flash accepts text input and supports tool calling, function calling, structured outputs and thinking; Gemini 2.0 Flash Exp Search accepts text and image input and supports web search, tool calling, function calling, structured outputs and long context.
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.
Related model match-ups readers also look at.