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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
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| Attribute | Qwen3.8 27Bqwen3.8-27b | Veo 3veo3 | Muse Spark 1.3muse-spark-1.3 | GLM 5.3glm-5.3 |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.45 / 1M | — | $1.25 / 1M | $1.40 / 1M |
| Output | $3.20 / 1M | — | $4.25 / 1M | $4.40 / 1M |
| Cache Write (5m) | $0.45 / 1M | Not applicable | $1.25 / 1M | $1.40 / 1M |
| Cache Write (1h) | $0.45 / 1M | Not applicable | $1.25 / 1M | $1.40 / 1M |
| Cache Read | $0.45 / 1M | Not applicable | $1.25 / 1M | $1.40 / 1M |
| Web Search | $0 / 1M | — | $0 / 1M | $0 / 1M |
| Request | — | $1.26 / request | — | — |
| Billing | — | Pay Per Request | — | — |
| Context | ||||
| Max context | 262K | N/A | 1M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | No | Yes | No |
| Function Calling | Yes | No | Yes | Yes |
| JSON Mode | Yes | No | Yes | Yes |
| Streaming | Yes | No | Yes | Yes |
| Catalogue | ||||
| Provider | Alibaba | Meta | Z.AI | |
| Category | chat | video | chat | chat |
| Charge type | Pay As You Go | Pay Per Request | 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 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. |