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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 3.1 Flash Lite Image (Google AI Studio)GoogleEnterprise & partner accessRemove
  2. GLM 5.3Z.AIRemove
  3. Muse Spark OpenMetaRemove
gemini-3.1-flash-lite-image-aistudio vs glm-5.3 vs muse-spark-open
AttributeGemini 3.1 Flash Lite Image (Google AI Studio)gemini-3.1-flash-lite-image-aistudioGLM 5.3glm-5.3Muse Spark Openmuse-spark-open
Pricing
Request$0.0336 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$1.40 / 1M$1.25 / 1M
Cache Write (1h)Not applicable$1.40 / 1M$1.25 / 1M
Cache ReadNot applicable$1.40 / 1M$1.25 / 1M
Input—$1.40 / 1M$1.25 / 1M
Output—$4.40 / 1M$4.25 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleZ.AIMeta
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released———
Description
SummaryGemini 3.1 Flash Lite Image served from Google AI Studio. 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.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.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.