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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. MiniMax M2MiniMaxRemove
  2. GPT-6 LunaOpenAIRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. Gemini 3.5 TranscribeGoogleRemove

4 is the maximum. Remove one to add another.

minimax-m2 vs gpt-6-luna vs perceptron-mk1.5 vs gemini-3.5-transcribe
AttributeMiniMax M2minimax-m2GPT-6 Lunagpt-6-lunaPerceptron Mk1.5perceptron-mk1.5Gemini 3.5 Transcribegemini-3.5-transcribe
Pricing
Input$0.15 / 1M$0.10 / 1M$0.15 / 1M— Not priced per input token
Output$0.45 / 1M$0.50 / 1M$1.50 / 1M— Not priced per output token
Cache Write (5m)$0.15 / 1M$0.10 / 1M$0.15 / 1MNot applicable
Cache Write (1h)$0.15 / 1M$0.10 / 1M$0.15 / 1MNot applicable
Cache Read$0.15 / 1M$0.10 / 1M$0.15 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context196.6K1.1M36.9K98.3K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoNo
StreamingYesYesYesNo
Catalogue
ProviderMiniMaxOpenAIPerceptronGoogle
Categorychatchatchatvoice
Charge typePay As You GoPay 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.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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.