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Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. S1Fish AudioRemove
  2. GPT-6 SolOpenAIRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

s1 vs gpt-6-sol vs perceptron-mk1.5 vs deepseek-v4.1-flash
AttributeS1s1GPT-6 Solgpt-6-solPerceptron Mk1.5perceptron-mk1.5DeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0 / 1M$2.00 / 1M$0.15 / 1M$0.30 / 1M
Output$0 / 1M$10.00 / 1M$1.50 / 1M$1.20 / 1M
Cache Write (5m)Not applicable$2.00 / 1M$0.15 / 1M$0.30 / 1M
Cache Write (1h)Not applicable$2.00 / 1M$0.15 / 1M$0.30 / 1M
Cache ReadNot applicable$2.00 / 1M$0.15 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1.1M36.9K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesNoYes
Function CallingNoYesNoYes
JSON ModeNoYesNoYes
StreamingNoYesYesYes
Catalogue
ProviderFish AudioOpenAIPerceptronDeepSeek
Categoryvoicechatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-07-29—2026-09-25—
Description
SummaryFish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.GPT-6 Sol is OpenAI's cost-efficient high-end model in the GPT-6 series, positioned between the flagship GPT-6 Astra and the fast GPT-6 Luna tier. It is designed for professional knowledge work, agentic coding, business workflow automation, and computer-use tasks, with particular strength in long-horizon software engineering across real-world codebases. GPT-6 Sol approaches Astra-level factual reliability at a significantly lower cost, while sharing its clear and concise communication style. This balance of capability, reliability, and efficiency makes it well suited for production agents, complex engineering workflows, and scalable professional applicationsPerceptron 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.