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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. Qwen3.8 27BAlibabaRemove
  2. Hy4 previewTencentRemove
  3. GPT-6 Luna ProOpenAIRemove
  4. Gemini 4 ArgonGoogleRemove

4 is the maximum. Remove one to add another.

qwen3.8-27b vs hy4-preview vs gpt-6-luna-pro vs gemini-4-argon
AttributeQwen3.8 27Bqwen3.8-27bHy4 previewhy4-previewGPT-6 Luna Progpt-6-luna-proGemini 4 Argongemini-4-argon
Pricing
Input$0.45 / 1M$0.834 / 1M$0.10 / 1M$2.00 / 1M
Output$3.20 / 1M$2.50 / 1M$0.50 / 1M$10.00 / 1M
Cache Write (5m)$0.45 / 1M$0.834 / 1M$0.10 / 1M$2.00 / 1M
Cache Write (1h)$0.45 / 1M$0.834 / 1M$0.10 / 1M$2.00 / 1M
Cache Read$0.45 / 1M$0.834 / 1M$0.10 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context262K1M1.1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderAlibabaTencentOpenAIGoogle
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
Description
SummaryQwen3.8 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.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.GPT-6 Luna Pro uses the same underlying model as GPT-6 Luna, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. It combines Luna's speed and cost efficiency with deeper reasoning and more reliable multi-step execution, making it well suited for advanced coding, computer use, and agentic workflows where higher solution quality is needed without moving to a larger GPT-6 tier.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.