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.

DeepSeek V4.1 FlashDeepSeek Remove
Perceptron Mk1.5Perceptron Remove
Qwen3 ASR 0.6BQwen Remove
GPT-6 LunaOpenAI Remove

4 is the maximum. Remove one to add another.

deepseek-v4.1-flash vs perceptron-mk1.5 vs qwen3-asr-0.6b vs gpt-6-luna
Attribute	DeepSeek V4.1 Flashdeepseek-v4.1-flash	Perceptron Mk1.5perceptron-mk1.5	Qwen3 ASR 0.6Bqwen3-asr-0.6b	GPT-6 Lunagpt-6-luna
Pricing
Input	$0.30 / 1M	$0.15 / 1M	$0 / 1M	$0.10 / 1M
Output	$1.20 / 1M	$1.50 / 1M	$0 / 1M	$0.50 / 1M
Cache Write (5m)	$0.30 / 1M	$0.15 / 1M	Not applicable	$0.10 / 1M
Cache Write (1h)	$0.30 / 1M	$0.15 / 1M	Not applicable	$0.10 / 1M
Cache Read	$0.30 / 1M	$0.15 / 1M	Not applicable	$0.10 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1M	36.9K	N/A	1.1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	No	No	Yes
Function Calling	Yes	No	No	Yes
JSON Mode	Yes	No	No	Yes
Streaming	Yes	Yes	No	Yes
Catalogue
Provider	DeepSeek	Perceptron	Qwen	OpenAI
Category	chat	chat	voice	chat
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	DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Qwen3-ASR 0.6B 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.