DeepSeek V4 Flash — AI Model Review & Pricing

by DeepSeek Intelligent Open Weight Coding Fast Rank #104 of 125

DeepSeek V4 Flash is an open-weight MoE model with 284B total parameters (13B activated), featuring hybrid attention for 10x KV cache efficiency and a 1M token context window. Released in preview on April 24, 2026, it (rank #97) and excels in high-throughput chat, coding, and agentic tasks at low cost.

Choose a model to compare against DeepSeek V4 Flash

Specifications

Specifications for DeepSeek V4 Flash
AttributeValue
Lab DeepSeek
Tags Intelligent Open Weight Coding Fast
Release Date 2026-03
Context Window 1,048,576 tokens
Input Price / 1M $0.10
Output Price / 1M $0.20
Input Modalities Text
Output Modalities Text

Strengths

  • 10x KV cache efficiency vs V3.2
  • 1,048,576 token context window
  • Three reasoning modes: Non-Think, Think High, Think Max
  • MIT license allows commercial use
  • Cost-effective at $0.10 input / $0.20 output per M tokens

Weaknesses

  • Chinese training bias affects non-Chinese tasks
  • Weaker than V4 Pro on complex reasoning and knowledge
  • Tends towards verbosity in outputs
  • Text-only; no multimodal support

Best For

  • High-throughput chat applications
  • Coding and code generation
  • Agentic tasks and tool use
  • Cost-sensitive production deployment

See what DeepSeek V4 Flash built

Interactive pages generated from the same creative briefs given to every model.

Explore all 3

In Depth: DeepSeek V4 Flash

Benchmark Performance

DeepSeek V4 Flash , placing it at rank #97 a strong mid-tier performer that punches above its weight in coding and agentic benchmarks, though trailing top contenders like the V4 Pro on complex reasoning.

In vendor-reported testing, DeepSeek V4 Flash achieves 91.6 on LiveCodeBench (Think Max mode) and 88.1 on GPQA Diamond (Think Max mode). These results highlight its coding and reasoning capabilities, though independent verification is pending. Its 13B activated parameters keep inference fast while maintaining competitive accuracy.

Pricing & Value

At $0.10 per million input tokens and $0.20 per million output tokens, DeepSeek V4 Flash is one of the most affordable models for high-volume production workloads.

Compared to similarly ranked peers, DeepSeek V4 Flash offers a price-per-point ratio of roughly $0.043 per million tokens per point (input) and $0.086 (output). This undercuts models like GPT-4o mini and Claude Haiku while delivering comparable context length and throughput, making it a standout choice for budget-conscious teams.

Who Should Use This

AI engineers deploying at scale. Chatbot builders needing long context. Developers on a budget. This model rewards those who value throughput and cost over raw benchmark dominance.

  • High-throughput API providers: low cost per token, but watch for verbosity in chat
  • Agentic coding tools: strong LiveCodeBench scores, but weaker on non-English tasks
  • Cost-conscious startups: MIT license and cheap API, but no multimodal input
  • Avoid if: you need state-of-the-art reasoning or native image/video support

Release & Version History

Released as a preview on April 24, 2026, DeepSeek V4 Flash introduced a new hybrid attention architecture and MoE design, marking a major architectural shift from the V3 family with a 10x KV cache improvement.

DeepSeek V4 Flash follows the DeepSeek V3 series (V3, V3.1, V3.2) and sits below the V4 Pro in the lineup. Its preview status signals ongoing refinement expect updates that may close the gap with V4 Pro on reasoning. The model is accessible via DeepSeek API, OpenRouter, or self-hosted on vLLM and Ollama.

Sources & Further Reading

Related Models