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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. Claude Opus 4.8AnthropicRemove
  2. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  3. Muse WonderMetaRemove
claude-opus-4-8 vs gemini-3.1-flash-image-vertex vs muse-wonder
AttributeClaude Opus 4.8claude-opus-4-8Gemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexMuse Wondermuse-wonder
Pricing
Input$5.00 / 1M—$4.00 / 1M
Output$25.00 / 1M—$20.00 / 1M
Cache Write (5m)$6.25 / 1MNot applicable$4.00 / 1M
Cache Write (1h)$10.00 / 1MNot applicable$4.00 / 1M
Cache Read$0.50 / 1MNot applicable$4.00 / 1M
Web Search$0 / 1M—$0 / 1M
Request—$0.067 / request—
Billing—Pay Per Request—
Context
Max context1MN/A1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderAnthropicGoogleMeta
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released———
Description
SummaryClaude Opus 4.8 is Anthropic's most capable generally available model in the Opus family, designed for highly autonomous agents, long-horizon workflows, and advanced knowledge work. It supports text, image, and file inputs with text output, includes reasoning capabilities, and features a 1M-token context window for maintaining coherence across extended tasks and sessions. The model excels at multi-step reasoning, complex coding, and end-to-end project orchestration, including large codebases, multi-stage debugging, and long-running asynchronous agent pipelines. Beyond software engineering, it is highly effective for document drafting, presentation creation, data analysis, and memory-driven workflows, delivering consistent quality across very long outputs and complex projects.Gemini 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.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.