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 | mai-ds-r1:freeNot in the catalogue | DeepSeek V4.1 Flashdeepseek-v4.1-flash | Perceptron Mk1.5perceptron-mk1.5 |
|---|---|---|---|
| Pricing | |||
| Input | — | $0.30 / 1M | $0.15 / 1M |
| Output | — | $1.20 / 1M | $1.50 / 1M |
| Cache Write (5m) | — | $0.30 / 1M | $0.15 / 1M |
| Cache Write (1h) | — | $0.30 / 1M | $0.15 / 1M |
| Cache Read | — | $0.30 / 1M | $0.15 / 1M |
| Web Search | — | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | — | 1M | 36.9K |
| Max output | — | N/A | N/A |
| Capabilities | |||
| Vision | — | Yes | No |
| Function Calling | — | Yes | No |
| JSON Mode | — | Yes | No |
| Streaming | — | Yes | Yes |
| Catalogue | |||
| Provider | — | DeepSeek | Perceptron |
| Category | — | chat | chat |
| Charge type | — | 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. | Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token. |