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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. Gemini 3.8 FlashGoogleRemove
  2. Qwen PlusAlibabaRemove
  3. GPT-6 AstraOpenAIRemove
  4. Muse Spark 1.3MetaRemove

4 is the maximum. Remove one to add another.

gemini-3.8-flash vs qwen-plus vs gpt-6-astra vs muse-spark-1.3
AttributeGemini 3.8 Flashgemini-3.8-flashQwen Plusqwen-plusGPT-6 Astragpt-6-astraMuse Spark 1.3muse-spark-1.3
Pricing
Input$0.75 / 1M$0.40 / 1M$10.00 / 1M$1.25 / 1M
Output$3.75 / 1M$1.20 / 1M$50.00 / 1M$4.25 / 1M
Cache Write (5m)$0.75 / 1M$0.40 / 1M$10.00 / 1M$1.25 / 1M
Cache Write (1h)$0.75 / 1M$0.40 / 1M$10.00 / 1M$1.25 / 1M
Cache Read$0.75 / 1M$0.40 / 1M$10.00 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M131.1K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderGoogleAlibabaOpenAIMeta
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 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.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.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.