Skip to content

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 Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  2. Gemini 4 ArgonGoogleRemove
  3. Muse Glimmer 30BMetaRemove
gemini-3.1-flash-image-vertex vs gemini-4-argon vs muse-glimmer-30b
AttributeGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexGemini 4 Argongemini-4-argonMuse Glimmer 30Bmuse-glimmer-30b
Pricing
Request$0.067 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$2.00 / 1M$0.35 / 1M
Cache Write (1h)Not applicable$2.00 / 1M$0.35 / 1M
Cache ReadNot applicable$2.00 / 1M$0.35 / 1M
Input—$2.00 / 1M$0.35 / 1M
Output—$10.00 / 1M$1.50 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A1M131K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleGoogleMeta
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released———
Description
SummaryGemini 3.1 Flash Image served from Google Vertex AI. Billed per image at US$0.067. 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 2K. A request for a larger size, such as 4K or 4096x4096, returns a 2K 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, for example 4096x4096->2048x2048.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It combines strong multi-step reasoning, reliable tool use, failure recovery, image understanding, and multilingual support across 100+ languages. Designed for long-horizon agentic and coding workflows, Muse Glimmer 30B offers a practical balance of capability and deployment efficiency, making it well suited for local coding assistants, multimodal agents, and production workflows that require sustained autonomous execution.