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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. Transcribe 1 ProFish AudioRemove
  2. GPT-6 LunaOpenAIRemove
  3. MiMo-V2-OmniXiaomiRemove
transcribe-1-pro vs gpt-6-luna vs mimo-v2-omni
AttributeTranscribe 1 Protranscribe-1-proGPT-6 Lunagpt-6-lunaMiMo-V2-Omnimimo-v2-omni
Pricing
Input— Not priced per input token$0.10 / 1M$0.40 / 1M
Output— Not priced per output token$0.50 / 1M$2.00 / 1M
Cache Write (5m)Not applicable$0.10 / 1M$0.40 / 1M
Cache Write (1h)Not applicable$0.10 / 1M$0.40 / 1M
Cache ReadNot applicable$0.10 / 1M$0.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1.1M262.1K
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderFish AudioOpenAIXiaomi
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-24——
Description
SummaryFish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.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.MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video, and audio inputs within a unified architecture. It combines strong multimodal perception with advanced agentic capabilities, including visual grounding, multi-step planning, tool use, and code execution. With a 256K context window, MiMo-V2-Omni is well suited for complex real-world tasks that span multiple modalities, enabling integrated reasoning and execution across diverse input types.