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.

MiMo-V2-OmniXiaomi Remove
Perceptron Mk1.5Perceptron Remove
Gemini 3.5 TranscribeGoogle Remove
GPT-6 LunaOpenAI Remove

4 is the maximum. Remove one to add another.

mimo-v2-omni vs perceptron-mk1.5 vs gemini-3.5-transcribe vs gpt-6-luna
Attribute	MiMo-V2-Omnimimo-v2-omni	Perceptron Mk1.5perceptron-mk1.5	Gemini 3.5 Transcribegemini-3.5-transcribe	GPT-6 Lunagpt-6-luna
Pricing
Input	$0.40 / 1M	$0.15 / 1M	— Not priced per input token	$0.10 / 1M
Output	$2.00 / 1M	$1.50 / 1M	— Not priced per output token	$0.50 / 1M
Cache Write (5m)	$0.40 / 1M	$0.15 / 1M	Not applicable	$0.10 / 1M
Cache Write (1h)	$0.40 / 1M	$0.15 / 1M	Not applicable	$0.10 / 1M
Cache Read	$0.40 / 1M	$0.15 / 1M	Not applicable	$0.10 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	262.1K	36.9K	98.3K	1.1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	No	Yes	Yes
Function Calling	Yes	No	Yes	Yes
JSON Mode	Yes	No	No	Yes
Streaming	Yes	Yes	No	Yes
Catalogue
Provider	Xiaomi	Perceptron	Google	OpenAI
Category	chat	chat	voice	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	2026-09-25	2026-09-25	—
Description
Summary	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.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.	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.