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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. MiniMax M2MiniMaxRemove
  2. Gemini 3.5 TranscribeGoogleRemove
  3. Perceptron Mk1.5PerceptronRemove
minimax-m2 vs gemini-3.5-transcribe vs perceptron-mk1.5
AttributeMiniMax M2minimax-m2Gemini 3.5 Transcribegemini-3.5-transcribePerceptron Mk1.5perceptron-mk1.5
Pricing
Input$0.15 / 1M— Not priced per input token$0.15 / 1M
Output$0.45 / 1M— Not priced per output token$1.50 / 1M
Cache Write (5m)$0.15 / 1MNot applicable$0.15 / 1M
Cache Write (1h)$0.15 / 1MNot applicable$0.15 / 1M
Cache Read$0.15 / 1MNot applicable$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context196.6K98.3K36.9K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesNoNo
StreamingYesNoYes
Catalogue
ProviderMiniMaxGooglePerceptron
Categorychatvoicechat
Charge typePay As You GoPay As You GoPay As You Go
Released—2026-09-252026-09-25
Description
SummaryMiniMax-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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.