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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. Grok 4.20 BetaxAIRemove
  3. GLM 5.3 FlashZ.AIRemove
deepseek-v4.1-flash vs grok-4.20-beta vs glm-5.3-flash
AttributeDeepSeek V4.1 Flashdeepseek-v4.1-flashGrok 4.20 Betagrok-4.20-betaGLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.30 / 1M$2.00 / 1M$0.075 / 1M
Output$1.20 / 1M$6.00 / 1M$0.25 / 1M
Cache Write (5m)$0.30 / 1M$2.00 / 1M$0.075 / 1M
Cache Write (1h)$0.30 / 1M$2.00 / 1M$0.075 / 1M
Cache Read$0.30 / 1M$2.00 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M2M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderDeepSeekxAIZ.AI
Categorychatchatchat
Charge typePay As You GoPay 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.Grok 4.20 Beta is xAI's newest flagship model, designed for high-performance reasoning with industry-leading speed and strong agentic tool-calling capabilities. It emphasizes strict prompt adherence and low hallucination rates, enabling highly reliable and precise responses across complex tasks. Optimized for agent workflows and real-time applications, Grok 4.20 Beta delivers consistent, truthful outputs while maintaining fast inference and strong task execution reliability.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.