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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. mai-ds-r1:freeNot in the catalogueRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. DeepSeek V4.1 Flash 1017DeepSeekRemove
mai-ds-r1:free vs perceptron-mk1.5 vs deepseek-v4.1-flash-1017
Attributemai-ds-r1:freeNot in the cataloguePerceptron Mk1.5perceptron-mk1.5DeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017
Pricing
Input—$0.15 / 1M$0.10 / 1M
Output—$1.50 / 1M$0.50 / 1M
Cache Write (5m)—$0.15 / 1M$0.10 / 1M
Cache Write (1h)—$0.15 / 1M$0.10 / 1M
Cache Read—$0.15 / 1M$0.10 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context—36.9K1M
Max output—N/AN/A
Capabilities
Vision—NoYes
Function Calling—NoYes
JSON Mode—NoYes
Streaming—YesYes
Catalogue
Provider—PerceptronDeepSeek
Category—chatchat
Charge type—Pay As You GoPay As You Go
Released—2026-09-25—
Description
Summary—Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek’s cost-efficient Mixture-of-Experts (MoE) model, built on its innovative Causal Encoder-Decoder (CED) architecture. Featuring 552B total parameters with 8B activated for input and 16B for output, it combines efficient inference with native multimodal understanding through jointly trained text and visual representations. Optimized for coding, terminal and computer-use agents, and long-horizon workflows, the model introduces compressed KV caching that reduces cache memory usage to approximately one-quarter of the previous Flash generation. DeepSeek reports that it surpasses V4 Pro in performance, inference speed, and task completion time, making it well suited for cost-efficient autonomous agents, complex software engineering, and long-context analysis.