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.
- mai-ds-r1:freeNot in the catalogueRemove
- Hy4 previewTencentRemove
- Gemini 3.5 TranscribeGoogleRemove
- Gemini 4 ArgonGoogleRemove
4 is the maximum. Remove one to add another.
| Attribute | mai-ds-r1:freeNot in the catalogue | Hy4 previewhy4-preview | Gemini 3.5 Transcribegemini-3.5-transcribe | Gemini 4 Argongemini-4-argon |
|---|---|---|---|---|
| Pricing | ||||
| Input | — | $0.834 / 1M | — Not priced per input token | $2.00 / 1M |
| Output | — | $2.50 / 1M | — Not priced per output token | $10.00 / 1M |
| Cache Write (5m) | — | $0.834 / 1M | Not applicable | $2.00 / 1M |
| Cache Write (1h) | — | $0.834 / 1M | Not applicable | $2.00 / 1M |
| Cache Read | — | $0.834 / 1M | Not applicable | $2.00 / 1M |
| Web Search | — | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | — | 1M | 98.3K | 1M |
| Max output | — | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | — | Yes | Yes | Yes |
| Function Calling | — | Yes | Yes | Yes |
| JSON Mode | — | Yes | No | Yes |
| Streaming | — | Yes | No | Yes |
| Catalogue | ||||
| Provider | — | Tencent | ||
| Category | — | chat | voice | chat |
| Charge type | — | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | 2026-09-25 | — |
| 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. | Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token. | Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response. |