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.
- Gemini 3.5 TranscribeGoogleRemove
- Transcribe 1 ProFish AudioRemove
- GPT-6 LunaOpenAIRemove
- MiniMax M2MiniMaxRemove
4 is the maximum. Remove one to add another.
| Attribute | Gemini 3.5 Transcribegemini-3.5-transcribe | Transcribe 1 Protranscribe-1-pro | GPT-6 Lunagpt-6-luna | MiniMax M2minimax-m2 |
|---|---|---|---|---|
| Pricing | ||||
| Input | — Not priced per input token | — Not priced per input token | $0.10 / 1M | $0.15 / 1M |
| Output | — Not priced per output token | — Not priced per output token | $0.50 / 1M | $0.45 / 1M |
| Cache Write (5m) | Not applicable | Not applicable | $0.10 / 1M | $0.15 / 1M |
| Cache Write (1h) | Not applicable | Not applicable | $0.10 / 1M | $0.15 / 1M |
| Cache Read | Not applicable | Not applicable | $0.10 / 1M | $0.15 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 98.3K | N/A | 1.1M | 196.6K |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | No | Yes | Yes |
| Function Calling | Yes | No | Yes | Yes |
| JSON Mode | No | No | Yes | Yes |
| Streaming | No | No | Yes | Yes |
| Catalogue | ||||
| Provider | Fish Audio | OpenAI | MiniMax | |
| Category | voice | voice | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | 2026-09-25 | 2026-09-24 | — | — |
| Description | ||||
| Summary | Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token. | Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio. | 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. | 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. |