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[ARTICLE · art-125501] src=zenmux.ai ↗ pub= topic=large-language-models verified=true sentiment=↑ positive

New Model Available: DeepSeek V4.1 Flash

DeepSeek released DeepSeek V4.1 Flash, a 552B-parameter mixture-of-experts model built on a new causal encoder-decoder architecture that natively supports multimodal visual understanding. The model is priced at $0.15-0.3 per million input tokens and $0.6-1.2 per million output tokens, with cache reads at 0.003-0.006 per million tokens, and is positioned for high-throughput, cost-sensitive agentic workloads through reduced KV cache requirements.

read1 min views5 publishedSep 10, 2026
New Model Available: DeepSeek V4.1 Flash
Image: Zenmux (auto-discovered)

DeepSeek V4.1 Flash is a 552B-parameter MoE model built on a new causal encoder-decoder architecture, designed for higher capability, faster reasoning, higher throughput, and lower serving cost. It natively supports multimodal visual understanding and delivers flagship-level intelligence with significantly reduced KV cache requirements, making it well suited for high-throughput and cost-sensitive agentic workloads.

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Providers #

Route requests across multiple providers. Copy a provider slug to set your preference.

$0.15-0.3

/ M tokens $0.6-1.2

/ M tokens Read:

0.003-0.006/ M tokens

Write:

-/ M tokens1M1.4s123tps

Uptime #

24hours Direct request success rate on AI Gateway and per-provider.

Throughput #

24hours P50 throughput on live AI Gateway traffic, in tokens per second (TPS).

Latency #

24hours P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds.

Activity #

Token volume and request traffic to this model over time.

Apps #

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for. View All

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