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.
- Hy4 previewTencentRemove
- Muse Spark 1.3MetaRemove
- GPT OSS 120BOpenAIRemove
- DeepSeek V4.1 FlashDeepSeekRemove
4 is the maximum. Remove one to add another.
| Attribute | Hy4 previewhy4-preview | Muse Spark 1.3muse-spark-1.3 | GPT OSS 120Bgpt-oss-120b | DeepSeek V4.1 Flashdeepseek-v4.1-flash |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.834 / 1M | $1.25 / 1M | $0.15 / 1M | $0.30 / 1M |
| Output | $2.50 / 1M | $4.25 / 1M | $0.75 / 1M | $1.20 / 1M |
| Cache Write (5m) | $0.834 / 1M | $1.25 / 1M | $0.15 / 1M | $0.30 / 1M |
| Cache Write (1h) | $0.834 / 1M | $1.25 / 1M | $0.15 / 1M | $0.30 / 1M |
| Cache Read | $0.834 / 1M | $1.25 / 1M | $0.15 / 1M | $0.30 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 1M | 1M | 131.1K | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | Yes | No | Yes |
| Function Calling | Yes | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Tencent | Meta | OpenAI | DeepSeek |
| 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 | 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. | 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. | gpt-oss-120b is an open-weight 117B-parameter MoE model from OpenAI, built for advanced reasoning and production workloads. Only about 5.1B parameters are active per step, and it’s optimized to run on a single H100 using MXFP4 quantization. It supports adjustable reasoning depth, full chain-of-thought, and native agent features like tool use, function calling, browsing, and structured outputs. | 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. |