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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. Qwen3 Coder NextAlibabaRemove
  2. GLM 5.3 FlashZ.AIRemove
  3. GPT-6 AstraOpenAIRemove
  4. Hy4 previewTencentRemove

4 is the maximum. Remove one to add another.

qwen3-coder-next vs glm-5.3-flash vs gpt-6-astra vs hy4-preview
AttributeQwen3 Coder Nextqwen3-coder-nextGLM 5.3 Flashglm-5.3-flashGPT-6 Astragpt-6-astraHy4 previewhy4-preview
Pricing
Input$0.175 / 1M$0.075 / 1M$10.00 / 1M$0.834 / 1M
Output$1.40 / 1M$0.25 / 1M$50.00 / 1M$2.50 / 1M
Cache Write (5m)$0.175 / 1M$0.075 / 1M$10.00 / 1M$0.834 / 1M
Cache Write (1h)$0.175 / 1M$0.075 / 1M$10.00 / 1M$0.834 / 1M
Cache Read$0.175 / 1M$0.075 / 1M$10.00 / 1M$0.834 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context262.1K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderAlibabaZ.AIOpenAITencent
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryQwen3-Coder-Next is an open-weight causal language model purpose-built for coding agents and local development workflows. It employs a sparse Mixture-of-Experts (MoE) architecture with 80B total parameters and only 3B activated per token, achieving performance comparable to models with 10–20× higher active compute. This efficiency makes it especially well suited for cost-sensitive, always-on agent deployments. Trained with a strong agentic focus, Qwen3-Coder-Next performs reliably on long-horizon coding tasks, complex tool interactions, and robust recovery from execution failures. With a native 256K context window, it integrates smoothly into real-world CLI and IDE environments and aligns well with common agent scaffolding used by modern coding tools. The model operates exclusively in non-thinking mode and does not emit <think> blocks, simplifying production integration for coding agents.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.GPT-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.