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 | Gemini 3.7 Flashgemini-3.7-flash | Muse Spark 1.3muse-spark-1.3 | Qwen3.5-122B-A10Bqwen3.5-122b-a10b | GLM 5.3glm-5.3 |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.375 / 1M | $1.25 / 1M | $0.40 / 1M | $1.40 / 1M |
| Output | $1.88 / 1M | $4.25 / 1M | $3.20 / 1M | $4.40 / 1M |
| Cache Write (5m) | $0.375 / 1M | $1.25 / 1M | $0.40 / 1M | $1.40 / 1M |
| Cache Write (1h) | $0.375 / 1M | $1.25 / 1M | $0.40 / 1M | $1.40 / 1M |
| Cache Read | $0.375 / 1M | $1.25 / 1M | $0.40 / 1M | $1.40 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 1M | 1M | 262.1K | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | Yes | Yes | No |
| Function Calling | Yes | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Meta | Alibaba | Z.AI | |
| Category | chat | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — | — |
| Description | ||||
| Summary | Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning. | 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. | Qwen3.5-122B-A10B is a native vision-language model built on a hybrid architecture that combines linear attention mechanisms with a sparse Mixture-of-Experts (MoE) design for improved inference efficiency. In overall performance, it ranks just below Qwen3.5-397B-A17B, delivering substantial gains over previous generations. Its text capabilities significantly exceed Qwen3-235B-2507, while its visual performance surpasses Qwen3-VL-235B, making it a strong high-end option for advanced multimodal and agent-driven applications. | 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. |