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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. GLM 4.6 (Thinking)Z.AIRemove
  2. DeepSeek V4.1 FlashDeepSeekRemove
  3. GPT-6 Astra ProOpenAIRemove
glm-4.6-thinking vs deepseek-v4.1-flash vs gpt-6-astra-pro
AttributeGLM 4.6 (Thinking)glm-4.6-thinkingDeepSeek V4.1 Flashdeepseek-v4.1-flashGPT-6 Astra Progpt-6-astra-pro
Pricing
Input$0.40 / 1M$0.30 / 1M$10.00 / 1M
Output$1.50 / 1M$1.20 / 1M$50.00 / 1M
Cache Write (5m)$0.40 / 1M$0.30 / 1M$10.00 / 1M
Cache Write (1h)$0.40 / 1M$0.30 / 1M$10.00 / 1M
Cache Read$0.40 / 1M$0.30 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context202.8K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderZ.AIDeepSeekOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-4.6 improves on GLM-4.5 with a larger 200K context window, stronger coding performance (including better real-world agent tools like Claude Code and Cline), and clearer gains in reasoning with built-in tool use. It delivers more capable agent behavior, integrates better into agent frameworks, and produces more natural, readable writing — especially in role-playing scenarios.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.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.