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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. DeepSeek V3.2 SpecialeDeepSeekRemove
  2. Muse WonderMetaRemove
  3. Gemini 3.1 Flash Lite Image (Google AI Studio)GoogleEnterprise & partner accessRemove
deepseek-v3.2-speciale vs muse-wonder vs gemini-3.1-flash-lite-image-aistudio
AttributeDeepSeek V3.2 Specialedeepseek-v3.2-specialeMuse Wondermuse-wonderGemini 3.1 Flash Lite Image (Google AI Studio)gemini-3.1-flash-lite-image-aistudio
Pricing
Input$0.28 / 1M$4.00 / 1M—
Output$0.40 / 1M$20.00 / 1M—
Cache Write (5m)$0.28 / 1M$4.00 / 1MNot applicable
Cache Write (1h)$0.28 / 1M$4.00 / 1MNot applicable
Cache Read$0.28 / 1M$4.00 / 1MNot applicable
Web Search$0 / 1M$0 / 1M—
Request——$0.0336 / request
Billing——Pay Per Request
Context
Max context163.8K1MN/A
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderDeepSeekMetaGoogle
Categorychatchatimage
Charge typePay As You GoPay As You GoPay Per Request
Released———
Description
SummaryDeepSeek-V3.2-Speciale is a high-compute edition of V3.2 built for top-tier reasoning and agent performance. Using DeepSeek Sparse Attention and extensive reinforcement learning, it surpasses GPT-5 on tough reasoning benchmarks and approaches Gemini 3 Pro–level capability, while still remaining strong at coding and tool use. It also draws on a large agent-training pipeline to boost reliability and generalization in interactive environments.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.Gemini 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.