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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. DeepSeek V4.1 FlashDeepSeekRemove
  2. Kimi K2 0711 Preview SearchMoonshot AIRemove
deepseek-v4.1-flash vs kimi-k2-0711-preview-search
AttributeDeepSeek V4.1 Flashdeepseek-v4.1-flashKimi K2 0711 Preview Searchkimi-k2-0711-preview-search
Pricing
Input$0.30 / 1M$0.165 / 1M
Output$1.20 / 1M$0.49 / 1M
Cache Write (5m)$0.30 / 1M$0.165 / 1M
Cache Write (1h)$0.30 / 1M$0.165 / 1M
Cache Read$0.30 / 1M$0.165 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M63K
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderDeepSeekMoonshot AI
Categorychatchat
Charge typePay As You GoPay As You Go
Released
Description
SummaryDeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.Kimi K2 Instruct is a trillion-parameter MoE model from Moonshot AI, with 32B active parameters per step. Built for strong agentic behavior, it excels at tool use, reasoning, and code generation, leading major benchmarks in coding, logic, and tool-use tasks. It supports up to 128K context and uses a specialized training setup (including MuonClip) to stabilize very large MoE training.