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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. Gemini 3.1 Flash Lite Image (Google Vertex AI)GoogleRemove
  2. Whisper 1OpenAIRemove
  3. Muse Spark OpenMetaRemove
gemini-3.1-flash-lite-image-vertex vs whisper-1 vs muse-spark-open
AttributeGemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertexWhisper 1whisper-1Muse Spark Openmuse-spark-open
Pricing
Request$0.0336 / request——
BillingPay Per Request——
Cache Write (5m)Not applicableNot applicable$1.25 / 1M
Cache Write (1h)Not applicableNot applicable$1.25 / 1M
Cache ReadNot applicableNot applicable$1.25 / 1M
Input—$75.00 / 1M$1.25 / 1M
Output—$75.00 / 1M$4.25 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/AN/A1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoNoYes
JSON ModeNoYesYes
StreamingNoNoYes
Catalogue
ProviderGoogleOpenAIMeta
Categoryimagevoicechat
Charge typePay Per RequestPay As You GoPay As You Go
Released———
Description
SummaryGemini 3.1 Flash Lite Image served from Google Vertex AI. Billed per image at US$0.0336. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 1K. A request for a larger size returns a 1K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size.Whisper (whisper-1) is OpenAI's open-source automatic speech recognition (ASR) model, designed for audio transcription and translation. It supports 50+ languages and processes audio files up to 25 MB, accepting formats such as mp3, mp4, wav, and webm. Optimized for reliable speech-to-text conversion across diverse audio inputs, Whisper is priced per minute of audio, billed to the nearest second, making it well suited for transcription, localization, and voice-driven applications.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.