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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 LunaOpenAIRemove
  2. Qwen3.8 27BAlibabaRemove
  3. Gemini 4 ArgonGoogleRemove
  4. Gemini 3.8 FlashGoogleRemove

4 is the maximum. Remove one to add another.

gpt-6-luna vs qwen3.8-27b vs gemini-4-argon vs gemini-3.8-flash
AttributeGPT-6 Lunagpt-6-lunaQwen3.8 27Bqwen3.8-27bGemini 4 Argongemini-4-argonGemini 3.8 Flashgemini-3.8-flash
Pricing
Input$0.10 / 1M$0.45 / 1M$2.00 / 1M$0.75 / 1M
Output$0.50 / 1M$3.20 / 1M$10.00 / 1M$3.75 / 1M
Cache Write (5m)$0.10 / 1M$0.45 / 1M$2.00 / 1M$0.75 / 1M
Cache Write (1h)$0.10 / 1M$0.45 / 1M$2.00 / 1M$0.75 / 1M
Cache Read$0.10 / 1M$0.45 / 1M$2.00 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.1M262K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderOpenAIAlibabaGoogleGoogle
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
Description
SummaryGPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.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.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.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.