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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 4 ArgonGoogleRemove
  2. mai-ds-r1:freeNot in the catalogueRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

gemini-4-argon vs mai-ds-r1:free vs perceptron-mk1.5 vs deepseek-v4.1-flash
AttributeGemini 4 Argongemini-4-argonmai-ds-r1:freeNot in the cataloguePerceptron Mk1.5perceptron-mk1.5DeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$2.00 / 1M—$0.15 / 1M$0.30 / 1M
Output$10.00 / 1M—$1.50 / 1M$1.20 / 1M
Cache Write (5m)$2.00 / 1M—$0.15 / 1M$0.30 / 1M
Cache Write (1h)$2.00 / 1M—$0.15 / 1M$0.30 / 1M
Cache Read$2.00 / 1M—$0.15 / 1M$0.30 / 1M
Web Search$0 / 1M—$0 / 1M$0 / 1M
Context
Max context1M—36.9K1M
Max outputN/A—N/AN/A
Capabilities
VisionYes—NoYes
Function CallingYes—NoYes
JSON ModeYes—NoYes
StreamingYes—YesYes
Catalogue
ProviderGoogle—PerceptronDeepSeek
Categorychat—chatchat
Charge typePay As You Go—Pay As You GoPay As You Go
Released——2026-09-25—
Description
SummaryGemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.—Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.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.