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Model details
DeepSeek: DeepSeek Pro Latest
DeepSeek Pro Latest functions as a rolling alias within DeepSeek's model lineup, designed to always redirect to the most recent release in the DeepSeek Pro family rather than pointing to a fixed version. This alias-style design lets users stay on the current top-tier DeepSeek Pro model without manually updating model identifiers. It is grouped in the same family alongside other always-current entries such as DeepSeek Flash Latest, and it sits within a broader DeepSeek catalog on OpenRouter that also includes fixed releases like DeepSeek V4.1 Flash, the company's first model built on the Causal Encoder-Decoder (CED) architecture. That CED context signals where the Pro family is heading: a sparse mixture-of-experts design with an asymmetric activation pattern that keeps per-token compute low relative to total parameters while natively handling image understanding.
In practical terms, DeepSeek Pro Latest is positioned as the flagship text-oriented endpoint for users who want the newest Pro-family capabilities as soon as DeepSeek ships them. Because the alias auto-redirects, long-running applications can rely on it to track forward-looking advancements in the Pro line without code changes, making it a good fit for production assistants, reasoning-heavy workloads, and tool-augmented workflows that benefit from staying current. Teams that need a pinned, reproducible model should instead select a specific DeepSeek Pro release, while those prioritizing freshness and a large context window for sustained multi-turn reasoning will get the most value from the Pro Latest pointer.
Quick Info
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- Kilo Gateway
- Model key
- ~deepseek/deepseek-pro-latest
- Release date
- Sep 14, 2026
- Last updated
- Sep 14, 2026
- Input modalities
- Output modalities
- Capabilities
Cost
- Input token cost
- $0.53328
- Output token cost
- $1.59984
Limits
- Output tokens
- 393,216 tokens
- Context window
- 1,048,576 tokens
Transparent token rates
Compare DeepSeek: DeepSeek Pro Latest pricing
Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
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