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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. Transcribe 1 ProFish AudioRemove
  2. Gemini 4 ArgonGoogleRemove
  3. Qwen3.8 27BAlibabaRemove
  4. Gemini 3.8 FlashGoogleRemove

4 is the maximum. Remove one to add another.

transcribe-1-pro vs gemini-4-argon vs qwen3.8-27b vs gemini-3.8-flash
AttributeTranscribe 1 Protranscribe-1-proGemini 4 Argongemini-4-argonQwen3.8 27Bqwen3.8-27bGemini 3.8 Flashgemini-3.8-flash
Pricing
Input— Not priced per input token$2.00 / 1M$0.45 / 1M$0.75 / 1M
Output— Not priced per output token$10.00 / 1M$3.20 / 1M$3.75 / 1M
Cache Write (5m)Not applicable$2.00 / 1M$0.45 / 1M$0.75 / 1M
Cache Write (1h)Not applicable$2.00 / 1M$0.45 / 1M$0.75 / 1M
Cache ReadNot applicable$2.00 / 1M$0.45 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M262K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderFish AudioGoogleAlibabaGoogle
Categoryvoicechatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-24———
Description
SummaryFish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.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.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 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.