Skip to content

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-Agent BetaxAIRemove
  3. GPT-6 LunaOpenAIRemove
gemini-3.5-transcribe vs grok-4.20-multi-agent-beta vs gpt-6-luna
AttributeGemini 3.5 Transcribegemini-3.5-transcribeGrok 4.20 Multi-Agent Betagrok-4.20-multi-agent-betaGPT-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 Beta 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 information synthesis to handle complex tasks. Optimized for deep research and multi-step problem solving, the model supports parallel reasoning, coordinated execution, and structured knowledge synthesis across large and complex workflows.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.