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.

GPT-6 LunaOpenAI Remove
Qwen3 ASR 0.6BQwen Remove
Muse Spark 1.3Meta Remove
Perceptron Mk1.5Perceptron Remove

4 is the maximum. Remove one to add another.

gpt-6-luna vs qwen3-asr-0.6b vs muse-spark-1.3 vs perceptron-mk1.5
Attribute	GPT-6 Lunagpt-6-luna	Qwen3 ASR 0.6Bqwen3-asr-0.6b	Muse Spark 1.3muse-spark-1.3	Perceptron Mk1.5perceptron-mk1.5
Pricing
Input	$0.10 / 1M	$0 / 1M	$1.25 / 1M	$0.15 / 1M
Output	$0.50 / 1M	$0 / 1M	$4.25 / 1M	$1.50 / 1M
Cache Write (5m)	$0.10 / 1M	Not applicable	$1.25 / 1M	$0.15 / 1M
Cache Write (1h)	$0.10 / 1M	Not applicable	$1.25 / 1M	$0.15 / 1M
Cache Read	$0.10 / 1M	Not applicable	$1.25 / 1M	$0.15 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1.1M	N/A	1M	36.9K
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	No	Yes	No
Function Calling	Yes	No	Yes	No
JSON Mode	Yes	No	Yes	No
Streaming	Yes	No	Yes	Yes
Catalogue
Provider	OpenAI	Qwen	Meta	Perceptron
Category	chat	voice	chat	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	2026-08-13	—	2026-09-25
Description
Summary	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.	Qwen3-ASR 0.6B speech-to-text. Billed per second of audio.	Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.