DeepSeek V4-Flash Undercuts Western Frontier Models on Cost, With a Token-Verbosity Caveat

Early analyses circulating among practitioners claim DeepSeek's V4-Flash completes some benchmark task suites at a total cost roughly 105 times lower than the leading Western frontier model, a figure that depends on both per-token price and how many tokens a model uses to finish a task.

The per-token side is not in dispute. Independent tracking lists V4-Flash at $0.14 per million input tokens and $0.28 per million output tokens, well under the market median of $0.58 and $2.20, and scores it around 50 on the Artificial Analysis Intelligence Index. It is an efficiency-tuned mixture-of-experts design with 284 billion total and roughly 13 billion active parameters, and it scores 82.7 on Terminal Bench 2.1 for agentic workloads, above DeepSeek's own V4-Pro preview.

The caveat is verbosity. The same tracking notes V4-Flash used about 210 million output tokens to complete the Intelligence Index, roughly 3.5 times the median, so an advertised per-token discount shrinks once the number of tokens a reasoning model uses is counted. The accurate measure is total task cost rather than per-token price, and on cost per completed task the model is cheap but not cheap by the full multiple its per-token rate implies.