# Runway — Real-Time Video at Batch Size One

- Company: Runway (runway.com)
- Announced: 2026-11-05T16:43:27.003000+00:00
- Category: research-paper
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://runway.com/news/research/real-time-video-at-batch-size-one
- Record: https://forck.live/items/32232-real-time-video-at-batch-size-one
- Subject: Gen / Aleph
- Models affected: Runway Characters

Runway published research on the serving system behind Runway Characters, a roughly 57B-parameter autoregressive video diffusion transformer that must generate a four-frame 704x1088 chunk every 166.7ms at 24 fps for a single user. Because each session is a private one-on-one stream needing 2.24 PFLOP/s, batching across users was not an option, so the team cut costs inside the step itself. Cache upkeep, which had consumed 69.7ms of a 239.2ms step, fell to 6.2ms after RoPE and FP8 quantization were applied once at write time and the cache was stored as a ring. Fusing the tensor-parallel all-reduce into the FP8 matrix multiplication hides 54-68% of its time, taking the fused call to 153.8µs against 208.2µs. Together the optimizations cut the diffusion step from 240.9ms to 159.3ms, or 24.5 fps on four H100s, and to 147.4ms with the fused kernel, down from eight H100s per session at launch. Over seven weeks of telemetry, the worker averaged above 23.5 fps in 99.5% of sessions streaming at least a second.

## Evidence

Verbatim from https://runway.com/news/research/real-time-video-at-batch-size-one:

> Every conversation has a rhythm. One person stops talking, the other starts and that back-and-forth pace sets the tone. We interrupt each other, talk over each other and bounce from topic to topic, staying on track the whole time. To be convincing — to cross the uncanny valley — a virtual character has to keep that same rhythm.
> 
> Runway Characters can turn a single image into a live character you can talk to, and behind it is a roughly 57B-parameter autoregressive video diffusion transformer. At 24 frames per second (fps), that model has to generate a new four-frame chunk of 704x1088 video every 166.7ms, for one user at a time, for as long as the conversation lasts.
> 
> In May, we first shared how we built Characters . In our new published research, Runway Characters: Serving a 57B Video Diffusion Transformer for Real-Time Conversation , we cover inference and the system that makes the rhythm behind this possible in production. We’ll give a high-level look at each below. The paper covers all of them in depth.
> 
> Key findings:
> 
> Characters launched on eight H100s per session. On four, the launch software took 240.9ms per diffusion step, well over the 166.7ms we require.

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Record: https://forck.live/items/32232-real-time-video-at-batch-size-one
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