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.
- Nemotron Nano 9B V2 (Free)NVIDIARemove
- Muse Spark 1.3MetaRemove
- GLM 5.3Z.AIRemove
- Hy4 previewTencentRemove
4 is the maximum. Remove one to add another.
| Attribute | Nemotron Nano 9B V2 (Free)nemotron-nano-9b-v2 | Muse Spark 1.3muse-spark-1.3 | GLM 5.3glm-5.3 | Hy4 previewhy4-preview |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0 / 1M | $1.25 / 1M | $1.40 / 1M | $0.834 / 1M |
| Output | $0 / 1M | $4.25 / 1M | $4.40 / 1M | $2.50 / 1M |
| Cache Write | $0 / 1M | — | — | — |
| Cache Read | $0 / 1M | $1.25 / 1M | $1.40 / 1M | $0.834 / 1M |
| Cache Write (5m) | — | $1.25 / 1M | $1.40 / 1M | $0.834 / 1M |
| Cache Write (1h) | — | $1.25 / 1M | $1.40 / 1M | $0.834 / 1M |
| Web Search | — | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 131.1K | 1M | 1M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | No | Yes | No | Yes |
| Function Calling | Yes | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | NVIDIA | Meta | Z.AI | Tencent |
| Category | chat | chat | chat | chat |
| Charge type | Free | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — | — |
| Description | ||||
| Summary | NVIDIA Nemotron Nano 9B v2 is a 9B-parameter language model trained from scratch by NVIDIA, designed to handle both reasoning and non-reasoning tasks. It can generate an internal reasoning trace before producing a final answer, and this behavior is configurable via system prompts—allowing developers to enable or suppress visible reasoning as needed. | 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. | Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows. |