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.
- Moonshot V1 32kMoonshot AIRemove
- DeepSeek V4.1 FlashDeepSeekRemove
- Muse Spark 1.3MetaRemove
- GLM 5.3Z.AIRemove
4 is the maximum. Remove one to add another.
| Attribute | Moonshot V1 32kmoonshot-v1-32k | DeepSeek V4.1 Flashdeepseek-v4.1-flash | Muse Spark 1.3muse-spark-1.3 | GLM 5.3glm-5.3 |
|---|---|---|---|---|
| Pricing | ||||
| Input | $3.29 / 1M | $0.30 / 1M | $1.25 / 1M | $1.40 / 1M |
| Output | $3.29 / 1M | $1.20 / 1M | $4.25 / 1M | $4.40 / 1M |
| Cache Write (5m) | $3.29 / 1M | $0.30 / 1M | $1.25 / 1M | $1.40 / 1M |
| Cache Write (1h) | $3.29 / 1M | $0.30 / 1M | $1.25 / 1M | $1.40 / 1M |
| Cache Read | $3.29 / 1M | $0.30 / 1M | $1.25 / 1M | $1.40 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 32K | 1M | 1M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | No | Yes | Yes | No |
| Function Calling | No | Yes | Yes | Yes |
| JSON Mode | No | Yes | Yes | Yes |
| Streaming | No | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Moonshot AI | DeepSeek | Meta | 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 | — | DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion. | 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. |