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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. Nemotron 3.5 Super VLNVIDIARemove
  3. Kimi K2 0905Moonshot AIRemove
kimi-k3.1-pro vs nemotron-3.5-super-vl vs kimi-k2-0905
AttributeKimi K3.1 Prokimi-k3.1-proNemotron 3.5 Super VLnemotron-3.5-super-vlKimi K2 0905kimi-k2-0905
Pricing
Input$2.00 / 1M$0.10 / 1M$0.60 / 1M
Output$10.00 / 1M$0.40 / 1M$2.50 / 1M
Cache Write (5m)$2.00 / 1M$0.10 / 1M$0.60 / 1M
Cache Write (1h)$2.00 / 1M$0.10 / 1M$0.60 / 1M
Cache Read$2.00 / 1M$0.10 / 1M$0.60 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M262K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMoonShot AINVIDIAMoonshot AI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
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.NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications.Kimi K2-Instruct-0905 is the newest and strongest Kimi K2 model — a trillion-parameter MoE system with 32B active parameters. It delivers major gains in agentic coding, better frontend development results, and an expanded 256K context window for longer tasks.