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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. inklingThinkingMachinesRemove
  2. Gemini 3.7 FlashGoogleRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
inkling vs gemini-3.7-flash vs deepseek-v4.1-flash
AttributeinklinginklingGemini 3.7 Flashgemini-3.7-flashDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0 / 1M$0.375 / 1M$0.30 / 1M
Output$0 / 1M$1.88 / 1M$1.20 / 1M
Cache Write$0 / 1M
Cache Read$0 / 1M$0.375 / 1M$0.30 / 1M
Cache Write (5m)$0.375 / 1M$0.30 / 1M
Cache Write (1h)$0.375 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderThinkingMachinesGoogleDeepSeek
Categorychatchatchat
Charge typeFreePay As You GoPay As You Go
Released
Description
SummaryInkling is a general-purpose multimodal autoregressive transformer model from Thinking Machines Lab, supporting text, image, and audio inputs with text output. It is designed for a wide range of applications, including reasoning, coding, multilingual understanding, and multimodal interaction. Optimized for agentic workflows, tool use, coding assistants, chatbots, retrieval-augmented generation (RAG), and instruction following, Inkling provides a versatile foundation for production AI systems requiring robust language and multimodal capabilities.Gemini 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 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.