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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 2.5 Flash Image (Nano Banana)GoogleRemove
  2. Claude Fable 5.2AnthropicRemove
  3. Muse WonderMetaRemove
gemini-2.5-flash-image vs claude-fable-5.2 vs muse-wonder
AttributeGemini 2.5 Flash Image (Nano Banana)gemini-2.5-flash-imageClaude Fable 5.2claude-fable-5.2Muse Wondermuse-wonder
Pricing
Input$0.30 / 1M$8.00 / 1M$4.00 / 1M
Output$2.50 / 1M$40.00 / 1M$20.00 / 1M
Cache Write (5m)Not applicable$10.00 / 1M$4.00 / 1M
Cache Write (1h)Not applicable$16.00 / 1M$4.00 / 1M
Cache ReadNot applicable$0.20 / 1M$4.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleAnthropicMeta
Categoryimagechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryGemini 2.5 Flash Image (“Nano Banana”) is now generally available. It’s a state-of-the-art image generation model with strong contextual understanding, supporting image creation, editing, and multi-turn conversational workflows around visuals.Claude Fable 5.2 is Anthropic's most capable model for advanced technical work and open-ended problem solving, delivering significant improvements in coding, reasoning, and vision over Fable 5.1. It excels at exceptionally complex tasks, including large-scale software migrations, electronic system design, and advanced scientific and mathematical research. With up to 30% faster output generation, clearer communication, and always-on adaptive extended thinking, Fable 5.2 supports configurable reasoning effort from low to max (default high), with thinking preserved across turns. Designed for frontier engineering, scientific discovery, and ambitious long-horizon agentic workflows, it complements Opus 5.5 as a specialized option for the most demanding technical challenges.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.