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 | Nemotron Nano 9B V2 (Free)nemotron-nano-9b-v2 | Gemini 4 Argongemini-4-argon |
|---|---|---|
| Pricing | ||
| Input | $0 / 1M | $2.00 / 1M |
| Output | $0 / 1M | $10.00 / 1M |
| Cache Write | $0 / 1M | — |
| Cache Read | $0 / 1M | $2.00 / 1M |
| Cache Write (5m) | — | $2.00 / 1M |
| Cache Write (1h) | — | $2.00 / 1M |
| Web Search | — | $0 / 1M |
| Context | ||
| Max context | 131.1K | 1M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | No | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | Yes | Yes |
| Catalogue | ||
| Provider | NVIDIA | |
| Category | chat | chat |
| Charge type | Free | 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. | 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. |