Skywork-R1V 38B for live video reasoning

What Skywork-R1V 38B is good at

Skywork-R1V 38B was built around chain-of-thought transfer, taking reasoning capability developed on text and carrying it into a vision-language model so the model works through a visual problem step by step rather than pattern-matching to a quick answer. That approach shows up most clearly on tasks with a defined correct answer, such as geometry, arithmetic, and logical puzzles presented as images.

Because the model is tuned for reasoning rather than raw scale, it can work through a multi-step visual math problem or a logic grid captured from a whiteboard or screen with more reliable intermediate steps than a general-purpose vision model of similar size.

• Chain-of-thought reasoning transferred into a vision model
• Strong performance on visual math and logic problems
• MIT-licensed 38B model for unrestricted self-hosting

Skywork-R1V 38B and the Overshoot workflow

Skywork-R1V 38B is not currently in Overshoot's live model catalog; GET /v1beta/models returns the current list. The workflow it would slot into is the standard one: publish a camera or screen share over WebRTC to open a Stream, then send a chat-completions request that references it with an ovs:// URL, the latest frame, an exact timestamp, or a recent segment. Overshoot retains 600 seconds of frame history, enough room to capture a whiteboard problem being worked through in real time.

Because Skywork-R1V 38B produces longer reasoning chains before answering, expect somewhat longer generations than a description-only model wherever it is served. On Overshoot, live models stream responses over SSE, so a client sees tokens as they are produced rather than waiting for a full chain-of-thought to finish, and a stable thread_id caches the shared parts of repeated prompts.

Skywork-R1V 38B among reasoning-focused vision models

Skywork-R1V 38B occupies a similar niche to QVQ-72B, another model built specifically for visual reasoning rather than general description, but at roughly half the parameter count. Teams working with math, logic, or diagram-heavy live video and wanting a smaller, self-hostable option often reach for Skywork-R1V 38B first, stepping up to a larger reasoning model only if accuracy on harder problems demands it.

Frequently asked questions

Can Skywork-R1V 38B analyze live video?

Skywork-R1V 38B reasons step by step over images and sampled video frames, but it is not currently in Overshoot's live model catalog. Live models answer questions about a WebRTC stream through ovs:// URLs, with reasoning and final answers streamed back over SSE. The catalog changes over time, so check GET /v1beta/models.

Is Skywork-R1V 38B open source?

Yes. Skywork-R1V 38B is released under the MIT license, one of the most permissive open licenses available, so its weights are freely downloadable and usable without the restrictions some other open models carry.

How is Skywork-R1V 38B different from a general vision-language model?

It was built by transferring chain-of-thought reasoning ability into a vision-language architecture, so it works through a visual problem step by step rather than answering directly. That makes it noticeably stronger on visual math and logic tasks than models tuned mainly for description.

What is Skywork-R1V 38B best used for?

It suits visual math, logic puzzles, and other problems captured on a whiteboard or screen where a step-by-step reasoning process improves accuracy, more than casual scene description or open-ended visual chat.

Related models

• QVQ-72B
• Emu3 8B
• InternVL3 78B
• GLM-4.5V