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. DeepSeek V3.2 SpecialeDeepSeekRemove
  2. GPT-6.1 TerraOpenAIRemove
  3. Gemini 4 ArgonGoogleRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

deepseek-v3.2-speciale vs gpt-6.1-terra vs gemini-4-argon vs muse-wonder
AttributeDeepSeek V3.2 Specialedeepseek-v3.2-specialeGPT-6.1 Terragpt-6.1-terraGemini 4 Argongemini-4-argonMuse Wondermuse-wonder
Pricing
Input$0.28 / 1M$1.00 / 1M$2.00 / 1M$4.00 / 1M
Output$0.40 / 1M$5.00 / 1M$10.00 / 1M$20.00 / 1M
Cache Write (5m)$0.28 / 1M$1.00 / 1M$2.00 / 1M$4.00 / 1M
Cache Write (1h)$0.28 / 1M$1.00 / 1M$2.00 / 1M$4.00 / 1M
Cache Read$0.28 / 1M$1.00 / 1M$2.00 / 1M$4.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context163.8K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesNoYesYes
Catalogue
ProviderDeepSeekOpenAIGoogleMeta
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
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.GPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost.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 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.