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.
4 is the maximum. Remove one to add another.
| Attribute | Veo 3veo3 | Qwen3.8 27Bqwen3.8-27b | Muse Spark 1.3muse-spark-1.3 | GLM 5.3 Flashglm-5.3-flash |
|---|---|---|---|---|
| Pricing | ||||
| Request | $1.26 / request | — | — | — |
| Billing | Pay Per Request | — | — | — |
| Cache Write (5m) | Not applicable | $0.45 / 1M | $1.25 / 1M | $0.075 / 1M |
| Cache Write (1h) | Not applicable | $0.45 / 1M | $1.25 / 1M | $0.075 / 1M |
| Cache Read | Not applicable | $0.45 / 1M | $1.25 / 1M | $0.075 / 1M |
| Input | — | $0.45 / 1M | $1.25 / 1M | $0.075 / 1M |
| Output | — | $3.20 / 1M | $4.25 / 1M | $0.25 / 1M |
| Web Search | — | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | N/A | 262K | 1M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | No | Yes | Yes | Yes |
| Function Calling | No | Yes | Yes | Yes |
| JSON Mode | No | Yes | Yes | Yes |
| Streaming | No | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Alibaba | Meta | Z.AI | |
| Category | video | chat | chat | chat |
| Charge type | Pay Per Request | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — | — |
| Description | ||||
| Summary | — | Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments. | 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. | 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. |