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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 AstraOpenAIRemove
  2. Qwen TurboAlibabaRemove
  3. Hy4 previewTencentRemove
  4. Qwen3.8 27BAlibabaRemove

4 is the maximum. Remove one to add another.

gpt-6-astra vs qwen-turbo vs hy4-preview vs qwen3.8-27b
AttributeGPT-6 Astragpt-6-astraQwen Turboqwen-turboHy4 previewhy4-previewQwen3.8 27Bqwen3.8-27b
Pricing
Input$10.00 / 1M$0.05 / 1M$0.834 / 1M$0.45 / 1M
Output$50.00 / 1M$0.20 / 1M$2.50 / 1M$3.20 / 1M
Cache Write (5m)$10.00 / 1M$0.05 / 1M$0.834 / 1M$0.45 / 1M
Cache Write (1h)$10.00 / 1M$0.05 / 1M$0.834 / 1M$0.45 / 1M
Cache Read$10.00 / 1M$0.05 / 1M$0.834 / 1M$0.45 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M262K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderOpenAIAlibabaTencentAlibaba
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.