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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. S2 ProFish AudioRemove
  2. Kimi K3.1 ProMoonShot AIRemove
  3. Gemini 4 CarbonGoogleRemove
s2-pro vs kimi-k3.1-pro vs gemini-4-carbon
AttributeS2 Pros2-proKimi K3.1 Prokimi-k3.1-proGemini 4 Carbongemini-4-carbon
Pricing
Input— Not priced per input token$2.00 / 1M$2.00 / 1M
Output— Not priced per output token$10.00 / 1M$10.00 / 1M
Cache Write (5m)Not applicable$2.00 / 1M$2.00 / 1M
Cache Write (1h)Not applicable$2.00 / 1M$2.00 / 1M
Cache ReadNot applicable$2.00 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderFish AudioMoonShot AIGoogle
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-07-29——
Description
SummaryFish Audio S2 Pro text-to-speech. Billed per UTF-8 byte of input text.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.Gemini 4 Carbon is Google's frontier multimodal reasoning model, designed for advanced coding, agentic workflows, and complex multi-step problem solving. It supports text, image, audio, video, and file inputs, enabling integrated reasoning and analysis across diverse modalities. Optimized for long-horizon execution and demanding professional workloads, Gemini 4 Carbon supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high) to balance reasoning depth, latency, and cost. It is well suited for autonomous agents, software engineering, multimodal analysis, and large-scale workflow automation.