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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. Kimi K3.1 ProMoonShot AIRemove
  2. GPT-6.1 TerraOpenAIRemove
  3. Gemma 4 26B A4B (Free)GoogleRemove
kimi-k3.1-pro vs gpt-6.1-terra vs gemma-4-26b-a4b-it:free
AttributeKimi K3.1 Prokimi-k3.1-proGPT-6.1 Terragpt-6.1-terraGemma 4 26B A4B (Free)gemma-4-26b-a4b-it:free
Pricing
Input$2.00 / 1M$1.00 / 1M$0 / 1M
Output$10.00 / 1M$5.00 / 1M$0 / 1M
Cache Write (5m)$2.00 / 1M$1.00 / 1M—
Cache Write (1h)$2.00 / 1M$1.00 / 1M—
Cache Read$2.00 / 1M$1.00 / 1M$0 / 1M
Web Search$0 / 1M$0 / 1M—
Cache Write——$0 / 1M
Context
Max context1M1M262.1K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesNoYes
Catalogue
ProviderMoonShot AIOpenAIGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoFree
Released———
Description
SummaryKimi 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.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.Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind, featuring 25.2B total parameters with only 3.8B activated per token—delivering near 31B-class quality at a fraction of the compute cost. It supports multimodal inputs including text, images, and video (up to 60s at 1fps). The model includes a 256K token context window, native function calling, configurable thinking/reasoning modes, and structured output support. Released under the Apache 2.0 license, it is well suited for efficient, production-ready multimodal and agentic applications.