# Jalapeño Posts Pareto Numbers on Open Models — OpenAI Is No Longer Only a Nvidia Tenant

Times of AI Desk · 2026-08-25 · Work

[https://timesof.ai/2026/08/openai-jalapeno-inference-chip-hot-chips](https://timesof.ai/2026/08/openai-jalapeno-inference-chip-hot-chips)

> OpenAI’s Engineering post reported the first measured InferenceX numbers for its first custom inference chip: 1.5–1.9× more AI work per watt at peak throughput and 1.7–3.6× lower end-to-end latency versus GB200/GB300. Lab-reported vs commercially shipping Blackwell; first-party deployment planned by year-end.

**Corrected October 14, 2026:** Removed an unsupported Broadcom co-development/June unveiling claim and an unsupported claim that SemiAnalysis verified runs on-site.

OpenAI is no longer only a **Nvidia tenant**. A **700 W** inference part that posts **Pareto** numbers on **open** models, programmed in part by **Astra**, is the lab’s bid to make **tokens per watt** an in-house lever before an IPO window.

**OpenAI** (Engineering / Company) published **“Jalapeño’s first results show industry-leading speed and efficiency in AI inference.”** The **inference-only** ASIC, now has **SemiAnalysis InferenceX** numbers against commercially available **Nvidia GB200 / GB300** racks. Across **GPT‑OSS 120B**, **DeepSeek R1 670B**, and **Kimi K2.5 1T**: **1.5–1.9×** more AI work per watt at peak throughput and **1.7–3.6×** lower end-to-end latency. Interactive workloads: **2.1–4.1×** higher performance. Package TDP **700 W**; measured sustained draw **≤550 W**. OpenAI will **start deploying Jalapeño in its own compute** by **end of 2026**. **Gen 2** is “deep in development”; **Gen 3** is “taking shape.” Nvidia GPUs remain in the mix for training and inference.

## What OpenAI published

| Item | openai.com Engineering Aug 25 |
|------|-------------------------------|
| **Chip** | **Jalapeño** — first custom **inference** ASIC |
| **Benchmark** | **InferenceX** (SemiAnalysis); public models, not only OpenAI weights |
| **Power basis** | Jalapeño **700 W** TDP vs GB200 **1,200 W** / GB300 **1,400 W** |
| **GPT‑OSS 120B** | ≈**1.9×** peak mixed TPS/kW (**85,448** vs **44,960**); ≈**1.7×** lower E2E latency |
| **DeepSeek R1** | ≈**1.7×** peak TPS/kW; ≈**3.6×** lower E2E (**1.65 s** vs **5.99 s**); min TBT ≈**4.1×** |
| **Kimi K2.5 1T** | ≈**1.5×** peak TPS/kW; ≈**3.4×** lower E2E |
| **Design loop** | Tape-out in **nine months**; Codex + **GPT‑Astra** brought three open-weight models to high performance in **two months** |
| **Caveat** | **Lab-reported** vs commercially shipping Blackwell; **not** a customer SKU; **not** a training chip |

Hot Chips coverage the same week (Tom’s Hardware, Bloomberg, Forbes) treats the Tuesday post as the primary. Nvidia is not a co-author; the comparison is OpenAI’s, using SemiAnalysis InferenceX methodology.

First-party silicon results are a **separate hardware lane** from Nvidia factory deals.

## Limits

- Numbers are **lab-reported** against commercially shipping Blackwell; not a customer SKU.
- OpenAI targets **end-2026** initial deployment — can slip.
- Whether **Vera Rubin / HBM4** comparisons replace today’s **Blackwell / HBM3E** slide is open.

## Sources

- [OpenAI: Jalapeño’s first results show industry-leading speed and efficiency in AI inference (August 25, 2026)](https://openai.com/index/jalapeno-first-results/)
- [Tom’s Hardware: OpenAI’s 700W Jalapeño ASIC outpaces 1,400W Nvidia flagship GPU (August 25, 2026)](https://www.tomshardware.com/tech-industry/semiconductors/openai-says-its-jalapeno-chip-beats-nvidias-gb300-in-first-published-benchmarks)
- [Bloomberg: OpenAI Claims Its New Chips Can Outperform Nvidia Processors in Tests (August 25, 2026)](https://www.bloomberg.com/news/articles/2026-08-25/openai-claims-its-new-chips-can-outperform-nvidia-processors-in-tests)