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.
- GLM 5.3 FlashZ.AIRemove
- Perceptron Mk1.5PerceptronRemove
- Gemini 4 ArgonGoogleRemove
- DeepSeek V4.1 FlashDeepSeekRemove
4 is the maximum. Remove one to add another.
| Attribute | GLM 5.3 Flashglm-5.3-flash | Perceptron Mk1.5perceptron-mk1.5 | Gemini 4 Argongemini-4-argon | DeepSeek V4.1 Flashdeepseek-v4.1-flash |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.075 / 1M | $0.15 / 1M | $2.00 / 1M | $0.30 / 1M |
| Output | $0.25 / 1M | $1.50 / 1M | $10.00 / 1M | $1.20 / 1M |
| Cache Write (5m) | $0.075 / 1M | $0.15 / 1M | $2.00 / 1M | $0.30 / 1M |
| Cache Write (1h) | $0.075 / 1M | $0.15 / 1M | $2.00 / 1M | $0.30 / 1M |
| Cache Read | $0.075 / 1M | $0.15 / 1M | $2.00 / 1M | $0.30 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 1M | 36.9K | 1M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | No | Yes | Yes |
| Function Calling | Yes | No | Yes | Yes |
| JSON Mode | Yes | No | Yes | Yes |
| Streaming | Yes | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Z.AI | Perceptron | DeepSeek | |
| Category | chat | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | 2026-09-25 | — | — |
| Description | ||||
| Summary | GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads. | Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token. | Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response. | 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. |