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.
| Attribute | Gemma 4 26B A4B (Free)gemma-4-26b-a4b-it:free | Hy4 previewhy4-preview | Muse Spark 1.3muse-spark-1.3 |
|---|---|---|---|
| Pricing | |||
| Input | $0 / 1M | $0.834 / 1M | $1.25 / 1M |
| Output | $0 / 1M | $2.50 / 1M | $4.25 / 1M |
| Cache Write | $0 / 1M | — | — |
| Cache Read | $0 / 1M | $0.834 / 1M | $1.25 / 1M |
| Cache Write (5m) | — | $0.834 / 1M | $1.25 / 1M |
| Cache Write (1h) | — | $0.834 / 1M | $1.25 / 1M |
| Web Search | — | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 262.1K | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | Yes |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Tencent | Meta | |
| Category | chat | chat | chat |
| Charge type | Free | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind, featuring 25.2B total parameters with only 3.8B activated per token—delivering near 31B-class quality at a fraction of the compute cost. It supports multimodal inputs including text, images, and video (up to 60s at 1fps). The model includes a 256K token context window, native function calling, configurable thinking/reasoning modes, and structured output support. Released under the Apache 2.0 license, it is well suited for efficient, production-ready multimodal and agentic applications. | 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. |