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.
| Attribute | Gemini 3 Flash Previewgemini-3-flash-preview | Muse Spark 1.3muse-spark-1.3 | GLM 5.3glm-5.3 |
|---|---|---|---|
| Pricing | |||
| Input | $0.25 / 1M | $1.25 / 1M | $1.40 / 1M |
| Output | $1.50 / 1M | $4.25 / 1M | $4.40 / 1M |
| Cache Write (5m) | $0.25 / 1M | $1.25 / 1M | $1.40 / 1M |
| Cache Write (1h) | $0.25 / 1M | $1.25 / 1M | $1.40 / 1M |
| Cache Read | $0.25 / 1M | $1.25 / 1M | $1.40 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1.0M | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | No |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Meta | Z.AI | |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Gemini 3 Flash Preview is a fast, cost-efficient reasoning model designed for agent workflows, multi-turn chat, and coding assistance. It offers near-Pro level reasoning and tool-use performance with significantly lower latency than larger Gemini models, making it ideal for interactive development and long-running agent loops. It improves on Gemini 2.5 Flash with stronger reasoning, multimodal understanding, and reliability. The model supports a 1M-token context window and multimodal inputs (text, images, audio, video, PDFs) with text outputs. It provides configurable reasoning levels, structured output formats, tool use, and automatic context caching—optimized for users seeking strong agentic reasoning without the cost or latency of full frontier-scale models. | 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 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution. |