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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. Whisper 1OpenAIRemove
  2. Gemini 3.1 Flash Lite Image (Google Vertex AI)GoogleRemove
  3. Muse Spark OpenMetaRemove
whisper-1 vs gemini-3.1-flash-lite-image-vertex vs muse-spark-open
AttributeWhisper 1whisper-1Gemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertexMuse Spark Openmuse-spark-open
Pricing
Input$75.00 / 1M—$1.25 / 1M
Output$75.00 / 1M—$4.25 / 1M
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
Web Search$0 / 1M—$0 / 1M
Request—$0.0336 / request—
Billing—Pay Per Request—
Context
Max contextN/AN/A1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoNoYes
JSON ModeYesNoYes
StreamingNoNoYes
Catalogue
ProviderOpenAIGoogleMeta
Categoryvoiceimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released———
Description
SummaryWhisper (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.Gemini 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.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.