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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. GPT-6 Astra ProOpenAIRemove
  2. Qwen3.8 27BAlibabaRemove
  3. Gemini 4 ArgonGoogleRemove
  4. Perceptron Mk1.5PerceptronRemove

4 is the maximum. Remove one to add another.

gpt-6-astra-pro vs qwen3.8-27b vs gemini-4-argon vs perceptron-mk1.5
AttributeGPT-6 Astra Progpt-6-astra-proQwen3.8 27Bqwen3.8-27bGemini 4 Argongemini-4-argonPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$10.00 / 1M$0.45 / 1M$2.00 / 1M$0.15 / 1M
Output$50.00 / 1M$3.20 / 1M$10.00 / 1M$1.50 / 1M
Cache Write (5m)$10.00 / 1M$0.45 / 1M$2.00 / 1M$0.15 / 1M
Cache Write (1h)$10.00 / 1M$0.45 / 1M$2.00 / 1M$0.15 / 1M
Cache Read$10.00 / 1M$0.45 / 1M$2.00 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M262K1M36.9K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesYes
Catalogue
ProviderOpenAIAlibabaGooglePerceptron
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released———2026-09-25
Description
SummaryGPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.Gemini 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.