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.

Perceptron Mk1.5Perceptron Remove
Transcribe 1 ProFish Audio Remove
GPT-6.1 SolOpenAI Remove
MiMo-V2-FlashXiaomi Remove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs transcribe-1-pro vs gpt-6.1-sol vs mimo-v2-flash
Attribute	Perceptron Mk1.5perceptron-mk1.5	Transcribe 1 Protranscribe-1-pro	GPT-6.1 Solgpt-6.1-sol	MiMo-V2-Flashmimo-v2-flash
Pricing
Input	$0.15 / 1M	— Not priced per input token	$2.00 / 1M	$0.09 / 1M
Output	$1.50 / 1M	— Not priced per output token	$10.00 / 1M	$0.29 / 1M
Cache Write (5m)	$0.15 / 1M	Not applicable	$2.00 / 1M	$0.09 / 1M
Cache Write (1h)	$0.15 / 1M	Not applicable	$2.00 / 1M	$0.09 / 1M
Cache Read	$0.15 / 1M	Not applicable	$2.00 / 1M	$0.09 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	36.9K	N/A	1M	262.1K
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	No	No	Yes	Yes
Function Calling	No	No	Yes	Yes
JSON Mode	No	No	Yes	Yes
Streaming	Yes	No	Yes	Yes
Catalogue
Provider	Perceptron	Fish Audio	OpenAI	Xiaomi
Category	chat	voice	chat	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	2026-09-25	2026-09-24	—	—
Description
Summary	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <\|speaker:0\|>. Billed per second of audio.	GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.	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.