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-FlashXiaomi Remove
Transcribe 1 ProFish Audio Remove
Perceptron Mk1.5Perceptron Remove
Gemini 3.5 TranscribeGoogle Remove

4 is the maximum. Remove one to add another.

mimo-v2-flash vs transcribe-1-pro vs perceptron-mk1.5 vs gemini-3.5-transcribe
Attribute	MiMo-V2-Flashmimo-v2-flash	Transcribe 1 Protranscribe-1-pro	Perceptron Mk1.5perceptron-mk1.5	Gemini 3.5 Transcribegemini-3.5-transcribe
Pricing
Input	$0.09 / 1M	— Not priced per input token	$0.15 / 1M	— Not priced per input token
Output	$0.29 / 1M	— Not priced per output token	$1.50 / 1M	— Not priced per output token
Cache Write (5m)	$0.09 / 1M	Not applicable	$0.15 / 1M	Not applicable
Cache Write (1h)	$0.09 / 1M	Not applicable	$0.15 / 1M	Not applicable
Cache Read	$0.09 / 1M	Not applicable	$0.15 / 1M	Not applicable
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	262.1K	N/A	36.9K	98.3K
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	No	No	Yes
Function Calling	Yes	No	No	Yes
JSON Mode	Yes	No	No	No
Streaming	Yes	No	Yes	No
Catalogue
Provider	Xiaomi	Fish Audio	Perceptron	Google
Category	chat	voice	chat	voice
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	2026-09-24	2026-09-25	2026-09-25
Description
Summary	MiMo-V2-Flash is an open-source Mixture-of-Experts (MoE) foundation model developed by Xiaomi, featuring 309B total parameters with 15B activated per token and a hybrid attention architecture. It supports a 256K context window and a hybrid thinking mode toggle, enabling flexible trade-offs between speed and reasoning depth. The model excels in reasoning, coding, and agentic workflows, ranking #1 globally among open-source models on benchmarks such as SWE-bench Verified and SWE-bench Multilingual. With performance comparable to leading proprietary models like Claude Sonnet 4.5 at a fraction of the cost, MiMo-V2-Flash is well suited for efficient, high-performance deployments.	Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <\|speaker:0\|>. Billed per second of audio.	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.