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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. Grok 4.6xAIRemove
  2. GPT-6 Astra ProOpenAIRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
grok-4.6 vs gpt-6-astra-pro vs deepseek-v4.1-flash
AttributeGrok 4.6grok-4.6GPT-6 Astra Progpt-6-astra-proDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$2.00 / 1M$10.00 / 1M$0.30 / 1M
Output$6.00 / 1M$50.00 / 1M$1.20 / 1M
Cache Write (5m)$2.00 / 1M$10.00 / 1M$0.30 / 1M
Cache Write (1h)$2.00 / 1M$10.00 / 1M$0.30 / 1M
Cache Read$2.00 / 1M$10.00 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context500K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderxAIOpenAIDeepSeek
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGrok 4.6 is SpaceXAI's smartest frontier model, delivering top-tier performance across coding, knowledge work, and STEM reasoning. It is designed for demanding technical and professional workloads that require strong problem solving, accurate instruction following, and reliable execution. Optimized for software engineering, scientific analysis, and complex knowledge tasks, Grok 4.6 is well suited for advanced coding, research, and agentic workflows where high capability and reasoning quality are critical.GPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.DeepSeek 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.