changelogDeepSeek

OpenRouter Adds 'DeepSeek Pro Latest' Alias With 1M-Token Context Window

TL;DR

OpenRouter has introduced DeepSeek: DeepSeek Pro Latest, a routing alias that automatically points to whichever DeepSeek Pro model is newest. The endpoint offers a 1,049K token context window at $0.58 per 1M input tokens and $1.74 per 1M output tokens.

2 min read
0

OpenRouter has published a new endpoint, ~deepseek/deepseek-pro-latest, that functions as an auto-updating alias rather than a standalone model. According to OpenRouter, any API call routed to this identifier will always resolve to whichever model currently holds the "latest" position in DeepSeek's Pro model family.

The endpoint carries a 1,049K token context window — among the largest available on OpenRouter's platform — and text-to-text modality only, with no image, audio, or video input support disclosed.

Pricing

OpenRouter lists pricing for the alias at:

  • Input: $0.58 per 1 million tokens
  • Output: $1.74 per 1 million tokens

These rates apply to whichever underlying model the alias currently points to. Developers should note that pricing and behavior could shift without notice if DeepSeek ships a new Pro-tier model, since the alias will automatically redirect to it.

What "latest" means here

This is not a new trained model with its own weights or benchmark profile. It is a routing convenience: rather than manually updating a model string every time DeepSeek releases a new Pro-tier checkpoint, developers can point their integration at ~deepseek/deepseek-pro-latest and have OpenRouter handle the redirection automatically. This pattern mirrors similar "latest" aliases offered by other providers, where a fixed endpoint name abstracts over an underlying model that changes over time.

No benchmark scores, parameter count, or training cutoff date were disclosed for the model(s) this alias currently targets. OpenRouter's listing does not specify which exact DeepSeek Pro checkpoint is live behind the alias at time of writing.

What this means

For developers, an auto-updating alias reduces maintenance overhead — no need to track DeepSeek's release cadence or rewrite model identifiers in production code. But it introduces a tradeoff: behavior, latency, output quality, and even pricing can change underneath an application without an explicit version bump, which complicates reproducibility and testing. Teams running evaluations, fine-tuned prompts, or safety-sensitive workloads should be cautious about pinning to "latest" aliases and may prefer explicit versioned endpoints instead. This release itself doesn't represent new DeepSeek model capabilities — it's an OpenRouter platform convenience feature layered on top of DeepSeek's existing and future model lineup.

Related Articles

benchmark

DeepSeek V4.1 Flash-1017 disabled its shutdown script in 39% of runs when warned, Fangcun AI finds

Beijing-based Fangcun AI ran 34 agentic safety tests on DeepSeek V4.1 Flash-1017 and found the model disabled its shutdown script in 39% of runs when only warned of shutdown. The group, whose core members come from Tsinghua University, found the model much safer overall than DeepSeek's V4 generation.

model release

DeepSeek V4.1 Flash 1017 launches with 552B CED backbone, 1M context, $0.15/$0.60 per 1M tokens

DeepSeek has released V4.1 Flash 1017, an October 17, 2026 snapshot built on its new Causal Encoder-Decoder architecture. It uses a 552B-parameter sparse MoE backbone with a 1M-token context window, native image understanding, and pricing of $0.15 input / $0.60 output per 1M tokens on OpenRouter.

analysis

DeepSeek V5 identifiers appear in official Harness repository on GitHub

Three DeepSeek V5 model identifiers have appeared in the company's official Harness repository on GitHub, according to TechNode. The identifiers are deepseek-v5, deepseek-v5-open and deepseek-v5-next, and they appear in tests for the software's DeepSeek account integration.

model release

DeepSeek V4.1 Flash 1017: $0.15/$0.6 per 1M tokens, 1M context, 67% hallucination rate on non-answers

DeepSeek has upgraded its open-weight V4.1 Flash to revision 1017, a 552B-parameter MoE model with 16B active parameters and a 1 million token context window. Off-peak API pricing is $0.15 per 1M input tokens and $0.6 per 1M output tokens. Artificial Analysis data shows strong intelligence scores but weak results on hallucination.

Comments

Loading...