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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. Gemini 3.8 FlashGoogleRemove
  2. Muse Spark 1.3MetaRemove
  3. DeepSeek V3.2 SpecialeDeepSeekRemove
gemini-3.8-flash vs muse-spark-1.3 vs deepseek-v3.2-speciale
AttributeGemini 3.8 Flashgemini-3.8-flashMuse Spark 1.3muse-spark-1.3DeepSeek V3.2 Specialedeepseek-v3.2-speciale
Pricing
Input$0.75 / 1M$1.25 / 1M$0.28 / 1M
Output$3.75 / 1M$4.25 / 1M$0.40 / 1M
Cache Write (5m)$0.75 / 1M$1.25 / 1M$0.28 / 1M
Cache Write (1h)$0.75 / 1M$1.25 / 1M$0.28 / 1M
Cache Read$0.75 / 1M$1.25 / 1M$0.28 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M163.8K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleMetaDeepSeek
Categorychatchatchat
Charge typePay 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.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.DeepSeek-V3.2-Speciale is a high-compute edition of V3.2 built for top-tier reasoning and agent performance. Using DeepSeek Sparse Attention and extensive reinforcement learning, it surpasses GPT-5 on tough reasoning benchmarks and approaches Gemini 3 Pro–level capability, while still remaining strong at coding and tool use. It also draws on a large agent-training pipeline to boost reliability and generalization in interactive environments.