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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

Gemma 4 31B (Free)Google Remove
Universal-3.5 ProAssemblyAI Remove
GPT-6 LunaOpenAI Remove

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gemma-4-31b-it:free vs universal-3-5-pro vs gpt-6-luna
Attribute	Gemma 4 31B (Free)gemma-4-31b-it:free	Universal-3.5 Prouniversal-3-5-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	Google	AssemblyAI	OpenAI
Category	chat	voice	chat
Charge type	Free	Pay As You Go	Pay As You Go
Released	—	2026-09-22	—
Description
Summary	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.	AssemblyAI Universal-3.5 Pro speech-to-text. 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.