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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. Muse Spark 1.3MetaRemove
  3. Qwen3.8 27BAlibabaRemove
transcribe-1-pro vs muse-spark-1.3 vs qwen3.8-27b
AttributeTranscribe 1 Protranscribe-1-proMuse Spark 1.3muse-spark-1.3Qwen3.8 27Bqwen3.8-27b
Pricing
Input— Not priced per input token$1.25 / 1M$0.45 / 1M
Output— Not priced per output token$4.25 / 1M$3.20 / 1M
Cache Write (5m)Not applicable$1.25 / 1M$0.45 / 1M
Cache Write (1h)Not applicable$1.25 / 1M$0.45 / 1M
Cache ReadNot applicable$1.25 / 1M$0.45 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M262K
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderFish AudioMetaAlibaba
Categoryvoicechatchat
Charge typePay 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.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.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.