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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. Qwen3.8 2.4T A95BAlibabaRemove
  3. Perceptron Mk1.5PerceptronRemove
gemini-4-argon vs qwen3.8-2.4t-a95b vs perceptron-mk1.5
AttributeGemini 4 Argongemini-4-argonQwen3.8 2.4T A95Bqwen3.8-2.4t-a95bPerceptron Mk1.5perceptron-mk1.5
Pricing
Input$2.00 / 1M$1.80 / 1M$0.15 / 1M
Output$10.00 / 1M$5.40 / 1M$1.50 / 1M
Cache Write (5m)$2.00 / 1M$1.80 / 1M$0.15 / 1M
Cache Write (1h)$2.00 / 1M$1.80 / 1M$0.15 / 1M
Cache Read$2.00 / 1M$1.80 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M262K36.9K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderGoogleAlibabaPerceptron
Categorychatchatchat
Charge typePay As You GoPay 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.Qwen3.8 2.4T A95B is Qwen's open-weight sparse Mixture-of-Experts (MoE) model and the open-weight counterpart to Qwen3.8 Max. It features 2.4T total parameters with 95B activated per token, combining frontier-scale capacity with efficient sparse inference. Designed for coding, research, complex reasoning, and agentic workflows, the model is well suited for demanding long-horizon tasks and advanced autonomous systems while providing the flexibility and customization benefits of open weights.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.