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.
| Attribute | Gemini 3.5 Transcribegemini-3.5-transcribe | Gemma 4 31B (Free)gemma-4-31b-it:free | GPT-6 Lunagpt-6-luna |
|---|---|---|---|
| Pricing | |||
| Input | — Not priced per input token | $0 / 1M | $0.10 / 1M |
| Output | — Not priced per output token | $0 / 1M | $0.50 / 1M |
| Cache Write (5m) | Not applicable | — | $0.10 / 1M |
| Cache Write (1h) | Not applicable | — | $0.10 / 1M |
| Cache Read | Not applicable | $0 / 1M | $0.10 / 1M |
| Web Search | $0 / 1M | — | $0 / 1M |
| Cache Write | — | $0 / 1M | — |
| Context | |||
| Max context | 98.3K | 262.1K | 1.1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | Yes |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | No | Yes | Yes |
| Streaming | No | Yes | Yes |
| Catalogue | |||
| Provider | OpenAI | ||
| Category | voice | chat | chat |
| Charge type | Pay As You Go | Free | Pay As You Go |
| Released | 2026-09-25 | — | — |
| Description | |||
| Summary | Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token. | Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model, supporting text and image inputs with text outputs. It features a 256K token context window, configurable thinking/reasoning modes, native function calling, and broad multilingual support across 140+ languages. The model delivers strong performance in coding, reasoning, and document understanding, making it well suited for developer workflows, multilingual applications, and structured knowledge tasks. | 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. |