Skip to content

Compare models

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

  1. GPT-6 Astra ProOpenAIRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. DeepSeek V4 ProDeepSeekRemove
gpt-6-astra-pro vs gemini-3.8-flash vs deepseek-v4-pro
AttributeGPT-6 Astra Progpt-6-astra-proGemini 3.8 Flashgemini-3.8-flashDeepSeek V4 Prodeepseek-v4-pro
Pricing
Input$10.00 / 1M$0.75 / 1M$0.435 / 1M
Output$50.00 / 1M$3.75 / 1M$0.87 / 1M
Cache Write (5m)$10.00 / 1M$0.75 / 1M$0.435 / 1M
Cache Write (1h)$10.00 / 1M$0.75 / 1M$0.435 / 1M
Cache Read$10.00 / 1M$0.75 / 1M$0.435 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1.0M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAIGoogleDeepSeek
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGPT-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.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.DeepSeek V4 Pro is a large-scale Mixture-of-Experts (MoE) model with 1.6T total parameters and 49B activated per token, supporting a 1M-token context window for advanced reasoning and long-horizon workflows. It delivers strong performance across knowledge, mathematics, and software engineering tasks, making it suitable for complex, real-world applications. Built on a hybrid attention architecture for efficient long-context processing, the model supports configurable reasoning modes to balance speed and depth. It is well suited for full codebase analysis, multi-step automation, and large-scale information synthesis, where both capability and efficiency are essential.https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro