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 | DeepSeek V4.1 Flashdeepseek-v4.1-flash | Gemini 3.5 Transcribegemini-3.5-transcribe | Gemini 4 Argongemini-4-argon |
|---|---|---|---|
| Pricing | |||
| Input | $0.30 / 1M | — Not priced per input token | $2.00 / 1M |
| Output | $1.20 / 1M | — Not priced per output token | $10.00 / 1M |
| Cache Write (5m) | $0.30 / 1M | Not applicable | $2.00 / 1M |
| Cache Write (1h) | $0.30 / 1M | Not applicable | $2.00 / 1M |
| Cache Read | $0.30 / 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 | DeepSeek | ||
| Category | chat | voice | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | 2026-09-25 | — |
| 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. | 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. |