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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. Perceptron Mk1.5PerceptronRemove
  3. GPT-6 LunaOpenAIRemove
  4. MiMo-V2-FlashXiaomiRemove

4 is the maximum. Remove one to add another.

transcribe-1-pro vs perceptron-mk1.5 vs gpt-6-luna vs mimo-v2-flash
AttributeTranscribe 1 Protranscribe-1-proPerceptron Mk1.5perceptron-mk1.5GPT-6 Lunagpt-6-lunaMiMo-V2-Flashmimo-v2-flash
Pricing
Input— Not priced per input token$0.15 / 1M$0.10 / 1M$0.09 / 1M
Output— Not priced per output token$1.50 / 1M$0.50 / 1M$0.29 / 1M
Cache Write (5m)Not applicable$0.15 / 1M$0.10 / 1M$0.09 / 1M
Cache Write (1h)Not applicable$0.15 / 1M$0.10 / 1M$0.09 / 1M
Cache ReadNot applicable$0.15 / 1M$0.10 / 1M$0.09 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A36.9K1.1M262.1K
Max outputN/AN/AN/AN/A
Capabilities
VisionNoNoYesYes
Function CallingNoNoYesYes
JSON ModeNoNoYesYes
StreamingNoYesYesYes
Catalogue
ProviderFish AudioPerceptronOpenAIXiaomi
Categoryvoicechatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-242026-09-25——
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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per 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.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.