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.
- Perceptron Mk1.5PerceptronRemove
- GPT-6 Luna ProOpenAIRemove
- MiniMax M2MiniMaxRemove
- Gemini 3.5 TranscribeGoogleRemove
4 is the maximum. Remove one to add another.
| Attribute | Perceptron Mk1.5perceptron-mk1.5 | GPT-6 Luna Progpt-6-luna-pro | MiniMax M2minimax-m2 | Gemini 3.5 Transcribegemini-3.5-transcribe |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.15 / 1M | $0.10 / 1M | $0.15 / 1M | — Not priced per input token |
| Output | $1.50 / 1M | $0.50 / 1M | $0.45 / 1M | — Not priced per output token |
| Cache Write (5m) | $0.15 / 1M | $0.10 / 1M | $0.15 / 1M | Not applicable |
| Cache Write (1h) | $0.15 / 1M | $0.10 / 1M | $0.15 / 1M | Not applicable |
| Cache Read | $0.15 / 1M | $0.10 / 1M | $0.15 / 1M | Not applicable |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 36.9K | 1.1M | 196.6K | 98.3K |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | No | Yes | Yes | Yes |
| Function Calling | No | Yes | Yes | Yes |
| JSON Mode | No | Yes | Yes | No |
| Streaming | Yes | Yes | Yes | No |
| Catalogue | ||||
| Provider | Perceptron | OpenAI | MiniMax | |
| Category | chat | chat | chat | voice |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | 2026-09-25 | — | — | 2026-09-25 |
| Description | ||||
| Summary | Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token. | GPT-6 Luna Pro uses the same underlying model as GPT-6 Luna, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. It combines Luna's speed and cost efficiency with deeper reasoning and more reliable multi-step execution, making it well suited for advanced coding, computer use, and agentic workflows where higher solution quality is needed without moving to a larger GPT-6 tier. | 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. |