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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 3.5 TranscribeGoogleRemove
  2. GPT-5.6 Sol ProOpenAIRemove
  3. Muse Spark 1.3MetaRemove
gemini-3.5-transcribe vs gpt-5.6-sol-pro vs muse-spark-1.3
AttributeGemini 3.5 Transcribegemini-3.5-transcribeGPT-5.6 Sol Progpt-5.6-sol-proMuse Spark 1.3muse-spark-1.3
Pricing
Input— Not priced per input token$5.00 / 1M$1.25 / 1M
Output— Not priced per output token$30.00 / 1M$4.25 / 1M
Cache Write (5m)Not applicable$5.00 / 1M$1.25 / 1M
Cache Write (1h)Not applicable$5.00 / 1M$1.25 / 1M
Cache ReadNot applicable$5.00 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context98.3K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleOpenAIMeta
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-25——
Description
SummaryGoogle Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.GPT-5.6 Sol Pro uses the same underlying model as GPT-5.6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning and more reliable execution, it is particularly well suited for advanced coding, long-horizon problem solving, and agentic workflows where accuracy and solution quality take priority over speed and cost.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.