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 SolOpenAI Remove
Perceptron Mk1.5Perceptron Remove
Muse Spark 1.3Meta Remove
Qwen3 ASR 0.6BQwen Remove

4 is the maximum. Remove one to add another.

gpt-6-sol vs perceptron-mk1.5 vs muse-spark-1.3 vs qwen3-asr-0.6b
Attribute	GPT-6 Solgpt-6-sol	Perceptron Mk1.5perceptron-mk1.5	Muse Spark 1.3muse-spark-1.3	Qwen3 ASR 0.6Bqwen3-asr-0.6b
Pricing
Input	$2.00 / 1M	$0.15 / 1M	$1.25 / 1M	$0 / 1M
Output	$10.00 / 1M	$1.50 / 1M	$4.25 / 1M	$0 / 1M
Cache Write (5m)	$2.00 / 1M	$0.15 / 1M	$1.25 / 1M	Not applicable
Cache Write (1h)	$2.00 / 1M	$0.15 / 1M	$1.25 / 1M	Not applicable
Cache Read	$2.00 / 1M	$0.15 / 1M	$1.25 / 1M	Not applicable
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1.1M	36.9K	1M	N/A
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	Yes	Yes	No
Catalogue
Provider	OpenAI	Perceptron	Meta	Qwen
Category	chat	chat	chat	voice
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	2026-09-25	—	2026-08-13
Description
Summary	GPT-6 Sol is OpenAI's cost-efficient high-end model in the GPT-6 series, positioned between the flagship GPT-6 Astra and the fast GPT-6 Luna tier. It is designed for professional knowledge work, agentic coding, business workflow automation, and computer-use tasks, with particular strength in long-horizon software engineering across real-world codebases. GPT-6 Sol approaches Astra-level factual reliability at a significantly lower cost, while sharing its clear and concise communication style. This balance of capability, reliability, and efficiency makes it well suited for production agents, complex engineering workflows, and scalable professional applications	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	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.	Qwen3-ASR 0.6B speech-to-text. Billed per second of audio.