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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. Universal-3.5 ProAssemblyAIRemove
  2. MiniMax M2MiniMaxRemove
  3. Transcribe 1 ProFish AudioRemove
  4. Perceptron Mk1.5PerceptronRemove

4 is the maximum. Remove one to add another.

universal-3-5-pro vs minimax-m2 vs transcribe-1-pro vs perceptron-mk1.5
AttributeUniversal-3.5 Prouniversal-3-5-proMiniMax M2minimax-m2Transcribe 1 Protranscribe-1-proPerceptron Mk1.5perceptron-mk1.5
Pricing
Input— Not priced per input token$0.15 / 1M— Not priced per input token$0.15 / 1M
Output— Not priced per output token$0.45 / 1M— Not priced per output token$1.50 / 1M
Cache Write (5m)Not applicable$0.15 / 1MNot applicable$0.15 / 1M
Cache Write (1h)Not applicable$0.15 / 1MNot applicable$0.15 / 1M
Cache ReadNot applicable$0.15 / 1MNot applicable$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A196.6KN/A36.9K
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesNoNo
Function CallingNoYesNoNo
JSON ModeNoYesNoNo
StreamingNoYesNoYes
Catalogue
ProviderAssemblyAIMiniMaxFish AudioPerceptron
Categoryvoicechatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-22—2026-09-242026-09-25
Description
SummaryAssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio.MiniMax-M2 is a compact, high-efficiency model with 10B active (230B total) parameters, optimized for coding and agentic workflows. It delivers near-frontier reasoning and tool use, excels at multi-file coding tasks and compile-run-fix loops, and performs strongly on benchmarks like SWE-Bench and Terminal-Bench. It also handles long-horizon planning and recovery in agent evaluations, ranking among the top open models across reasoning domains. With fast inference and low cost, it’s ideal for large-scale agents and developer assistants — and works best when reasoning is preserved across turns.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.