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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 3.7 FlashGoogleRemove
  2. DeepSeek V3.2 (Thinking)DeepSeekRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
gemini-3.7-flash vs deepseek-v3.2-thinking vs deepseek-v4.1-flash
AttributeGemini 3.7 Flashgemini-3.7-flashDeepSeek V3.2 (Thinking)deepseek-v3.2-thinkingDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0.375 / 1M$0.19 / 1M$0.30 / 1M
Output$1.88 / 1M$0.275 / 1M$1.20 / 1M
Cache Write (5m)$0.375 / 1M$0.19 / 1M$0.30 / 1M
Cache Write (1h)$0.375 / 1M$0.19 / 1M$0.30 / 1M
Cache Read$0.375 / 1M$0.19 / 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 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.DeepSeek-V3.2 is an efficiency-focused large model that combines strong reasoning with reliable tool use. It introduces DeepSeek Sparse Attention to lower compute costs for long contexts while preserving quality, and uses large-scale reinforcement learning to reach GPT-5-class reasoning (including top IMO/IOI results). An agentic task-synthesis pipeline improves how it reasons with tools in interactive settings — and developers can toggle reasoning on or off as needed.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.