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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. GPT-6.1 TerraOpenAIRemove
  2. Gemini Embedding 2GoogleRemove
  3. Kimi K3.1 ProMoonShot AIRemove
gpt-6.1-terra vs gemini-embedding-2-preview vs kimi-k3.1-pro
AttributeGPT-6.1 Terragpt-6.1-terraGemini Embedding 2gemini-embedding-2-previewKimi K3.1 Prokimi-k3.1-pro
Pricing
Input$1.00 / 1M$0.60 / 1M$2.00 / 1M
Output$5.00 / 1M$2.40 / 1M$10.00 / 1M
Cache Write (5m)$1.00 / 1M$0.60 / 1M$2.00 / 1M
Cache Write (1h)$1.00 / 1M$0.60 / 1M$2.00 / 1M
Cache Read$1.00 / 1M$0.60 / 1M$2.00 / 1M
Web Search$0 / 1M—$0 / 1M
Context
Max context1M8.2K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesNoYes
StreamingNoNoYes
Catalogue
ProviderOpenAIGoogleMoonShot AI
Categorychatembeddingchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryGPT-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 Embedding 2 is Google's advanced text embedding model designed for high-accuracy semantic representation across large-scale retrieval and understanding tasks. It converts text into dense vector embeddings optimized for semantic search, retrieval-augmented generation (RAG), clustering, classification, and recommendation systems. Built for production use, it offers strong multilingual support, improved semantic similarity accuracy, and efficient embedding generation, making it well suited for large knowledge indexing pipelines and enterprise-scale retrieval applications.Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution.