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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. Gemini 3.5 TranscribeGoogleRemove
  2. Grok 4.20 Multi-AgentxAIRemove
  3. GPT-6 LunaOpenAIRemove
gemini-3.5-transcribe vs grok-4.20-multi-agent vs gpt-6-luna
AttributeGemini 3.5 Transcribegemini-3.5-transcribeGrok 4.20 Multi-Agentgrok-4.20-multi-agentGPT-6 Lunagpt-6-luna
Pricing
Input— Not priced per input token$2.00 / 1M$0.10 / 1M
Output— Not priced per output token$6.00 / 1M$0.50 / 1M
Cache Write (5m)Not applicable$2.00 / 1M$0.10 / 1M
Cache Write (1h)Not applicable$2.00 / 1M$0.10 / 1M
Cache ReadNot applicable$2.00 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context98.3K2M1.1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGooglexAIOpenAI
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-25——
Description
SummaryGoogle Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Grok 4.20 Multi-Agent is a specialized variant of xAI's Grok 4.20 designed for collaborative, agent-based workflows. It enables multiple agents to operate in parallel, coordinating tool use and synthesizing information to handle complex, multi-step tasks. Optimized for deep research and large-scale problem solving, the model supports configurable reasoning effort: 4 agents for low/medium settings and up to 16 agents for high/xhigh settings, enabling scalable parallel reasoning and execution.GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.