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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. MiniMax M2MiniMaxRemove
  3. Gemini 3.5 TranscribeGoogleRemove
transcribe-1-pro vs minimax-m2 vs gemini-3.5-transcribe
AttributeTranscribe 1 Protranscribe-1-proMiniMax M2minimax-m2Gemini 3.5 Transcribegemini-3.5-transcribe
Pricing
Input— Not priced per input token$0.15 / 1M— Not priced per input token
Output— Not priced per output token$0.45 / 1M— Not priced per output token
Cache Write (5m)Not applicable$0.15 / 1MNot applicable
Cache Write (1h)Not applicable$0.15 / 1MNot applicable
Cache ReadNot applicable$0.15 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A196.6K98.3K
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesNo
StreamingNoYesNo
Catalogue
ProviderFish AudioMiniMaxGoogle
Categoryvoicechatvoice
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-24—2026-09-25
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.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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.