# DeepSeek ships V4: 1.6T open-weight model, $1.74 a million tokens

> DeepSeek released V4-Pro (1.6T params) and V4-Flash (284B) on 24 April 2026 under MIT.

*The brief: two MIT-licensed MoE models, 1M context, and the first DeepSeek architecture built for Huawei chips.*

By The FeaturedDaily Desk · FeaturedDaily
Canonical: https://featureddaily.com/news/deepseek-v4-brief

> **Key:** **The brief:** DeepSeek's V4 is a real open-weight leap — the largest available, the cheapest at its tier, and the first built on domestic Chinese silicon. The context window jump (128K → 1M) and the inference efficiency gain (27% of V3.2's FLOPs) are the durable numbers.

## What happened

On **24 April 2026** DeepSeek released two Mixture-of-Experts models under MIT: **V4-Pro** (1.6T total / 49B active parameters) and **V4-Flash** (284B / 13B active). Both support a **1 million-token context window** — up from 128K in V3.2 — and a 384K max output. Weights are live on Hugging Face; the API went live the same day. The legacy `deepseek-chat` and `deepseek-reasoner` model IDs will be retired **24 July 2026**, mapping to V4-Flash in the interim. A new sparse-attention architecture (CSA + HCA) cuts V4-Pro's inference FLOPs to **27% of V3.2** and KV-cache to 10%.

## The numbers: benchmarks and price

Artificial Analysis placed V4-Pro **#2 on the open-weight reasoning index** (behind Kimi K2.6) and leading open models on agentic coding. Standard API pricing: V4-Pro **$1.74/M input / $3.48/M output** (launched on a 75% promo at $0.435/$0.87); V4-Flash **$0.14/M input / $0.28/M output**. CFR put the overall U.S. AI lead at roughly seven months — but noted the competitive contest is adoption scale, not just leaderboard rank.

| | V4-Pro | V4-Flash | V3.2 (prev.) |
| --- | --- | --- | --- |
| Params (total / active) | 1.6T / 49B | 284B / 13B | 671B / 37B |
| Context | 1M tokens | 1M tokens | 128K tokens |
| API input price (list) | $1.74/M | $0.14/M | $0.27/M |
| Inference FLOPs | 27% of V3.2 | ~10% of V3.2 | baseline |

> CFR fellow Michael Horowitz observed that 'second-best models carry enormous competitive value when they are cheap and open, which makes them easy to widely diffuse' — reframing the contest from benchmark supremacy to global deployment reach.
> — [Council on Foreign Relations](https://www.cfr.org/articles/deepseek-v4-signals-a-new-phase-in-the-u-s-china-ai-rivalry), 2026-04-29

**What to watch.** Whether DeepSeek publishes a technical paper (the efficiency claims are plausible but currently self-reported). Whether inference on Huawei Ascend proves cost-competitive with Nvidia at scale. Whether V4's MIT licence accelerates global adoption outside the U.S. — the strategic variable the leaderboard doesn't capture.

## Key takeaways

- DeepSeek released V4-Pro (1.6T total / 49B active params) and V4-Flash (284B / 13B active) on 24 April 2026, MIT-licensed, on Hugging Face.
- Both models support 1M-token context windows — an 8× jump over V3.2's 128K limit.
- API pricing: V4-Pro lists at $1.74/M input (launched on a 75% promo at $0.435/M), V4-Flash $0.14/M — a fraction of U.S. closed-frontier rates.
- V4 is the first DeepSeek model built for Huawei Ascend chips; DeepSeek reportedly gave early access only to Chinese chipmakers.

## FAQ

### What did DeepSeek release on 24 April 2026?
Two open-weight Mixture-of-Experts models: V4-Pro (1.6T total / 49B active parameters) and V4-Flash (284B / 13B active). Both are MIT-licensed with 1M-token context windows, published on Hugging Face.

### How much does DeepSeek V4 cost via API?
V4-Pro lists at $1.74/M input, $3.48/M output (it launched on a 75% promo at $0.435/$0.87). V4-Flash: $0.14/M input, $0.28/M output. Both are self-hostable for free under the MIT licence.

### Is DeepSeek V4 better than GPT-5 or Claude?
Not at the top of the capability range — CFR put the overall U.S. AI lead at roughly seven months. Artificial Analysis placed V4-Pro #2 among open-weight reasoning models (DeepSeek's own report claims it leads LiveCodeBench at 93.5 vs Claude Opus 4.6's 88.8, a self-reported figure that isn't yet independently confirmed). It is, however, the most capable model you can self-host, and significantly cheaper via API than U.S. closed-frontier equivalents.

## Sources

- [DeepSeek V4 Preview Release](https://api-docs.deepseek.com/news/news260424) — DeepSeek, 2026-04-24
- [Three reasons why DeepSeek's new model matters](https://www.technologyreview.com/2026/04/24/1136422/why-deepseeks-v4-matters/) — MIT Technology Review, 2026-04-24
- [DeepSeek is back among the leading open-weights models with V4 Pro and V4 Flash](https://artificialanalysis.ai/articles/deepseek-is-back-among-the-leading-open-weights-models-with-v4-pro-and-v4-flash) — Artificial Analysis, 2026-04-27
- [DeepSeek V4 signals a new phase in the US–China AI rivalry](https://www.cfr.org/articles/deepseek-v4-signals-a-new-phase-in-the-u-s-china-ai-rivalry) — Council on Foreign Relations, 2026-04-29
- [DeepSeek previews new AI model that 'closes the gap' with frontier models](https://techcrunch.com/2026/04/24/deepseek-previews-new-ai-model-that-closes-the-gap-with-frontier-models/) — TechCrunch, 2026-04-24