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 | Gemma 4 26B A4B (Free)gemma-4-26b-a4b-it:free | Transcribe 1 Protranscribe-1-pro | GPT-6 Lunagpt-6-luna |
|---|---|---|---|
| Pricing | |||
| Input | $0 / 1M | — Not priced per input token | $0.10 / 1M |
| Output | $0 / 1M | — Not priced per output token | $0.50 / 1M |
| Cache Write | $0 / 1M | — | — |
| Cache Read | $0 / 1M | Not applicable | $0.10 / 1M |
| Cache Write (5m) | — | Not applicable | $0.10 / 1M |
| Cache Write (1h) | — | Not applicable | $0.10 / 1M |
| Web Search | — | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 262.1K | N/A | 1.1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | No | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | Fish Audio | OpenAI | |
| Category | chat | voice | chat |
| Charge type | Free | Pay As You Go | Pay As You Go |
| Released | — | 2026-09-24 | — |
| Description | |||
| Summary | Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind, featuring 25.2B total parameters with only 3.8B activated per token—delivering near 31B-class quality at a fraction of the compute cost. It supports multimodal inputs including text, images, and video (up to 60s at 1fps). The model includes a 256K token context window, native function calling, configurable thinking/reasoning modes, and structured output support. Released under the Apache 2.0 license, it is well suited for efficient, production-ready multimodal and agentic applications. | 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. |