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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. DeepSeek V3.2 SpecialeDeepSeekRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
gemini-3.8-flash vs deepseek-v3.2-speciale vs deepseek-v4.1-flash
AttributeGemini 3.8 Flashgemini-3.8-flashDeepSeek V3.2 Specialedeepseek-v3.2-specialeDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0.75 / 1M$0.28 / 1M$0.30 / 1M
Output$3.75 / 1M$0.40 / 1M$1.20 / 1M
Cache Write (5m)$0.75 / 1M$0.28 / 1M$0.30 / 1M
Cache Write (1h)$0.75 / 1M$0.28 / 1M$0.30 / 1M
Cache Read$0.75 / 1M$0.28 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M163.8K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleDeepSeekDeepSeek
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.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.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.