Tracker comparison · Deep OC-SORT vs OC-SORT
Deep OC-SORT vs OC-SORT
A head-to-head of Deep OC-SORT and OC-SORT for multi-object tracking behind YOLO: how fast each runs across 10 NVIDIA GPUs and how steadily it holds object IDs, measured on the same clip and the same detector.
The verdict: On an NVIDIA H100, Deep OC-SORT is the quicker of the two at 101 FPS versus 55 for OC-SORT, roughly 1.8× its throughput, and it stays out front on all 10 GPU tiers. Deep OC-SORT is the steadier tracker: 42 ID fragmentations against 113 for OC-SORT (63% fewer), across 12 unique IDs to 79 on the same clip. That hands Deep OC-SORT both the speed and the cleaner IDs on this hardware, making it the safer default: step up to OC-SORT for simple, sparse scenes with little occlusion.
Higher FPS on 10 of the 10 GPU tiers tested.
Only 42 ID fragmentations, versus 113 for OC-SORT.
ID-stability: what a fragmentation actually looks like
How well a tracker holds a single, consistent ID on each object is a property of the algorithm, not the GPU, so these numbers barely move across hardware; we report them once (measured on the NVIDIA H100). This clip has no MOT ground truth, so instead of MOTA/IDF1 we report the raw stability signals: how many distinct IDs the tracker created, how many times a track was broken (fragmentations), and the average track length. Fewer IDs and fewer fragmentations mean steadier identities.
| Tracker | Approach | Unique IDs | Fragmentations | Avg track length |
|---|---|---|---|---|
| Deep OC-SORT | Motion + Re-ID | 12 | 42 | 80.4 |
| OC-SORT | Motion only | 79 | 113 | 29.6 |
Speed by GPU
Deep OC-SORT and OC-SORT, ranked fastest-first. Pick any GPU to see which one leads on that hardware. End-to-end detection + tracking throughput (frames per second, higher is better) for Deep OC-SORT and OC-SORT across all 10 GPU tiers. GPUs are ordered flagship-first.
- Deep OC-SORT
- OC-SORT
Tip: Bold marks the faster tracker on each GPU. Measured with yolo26n.pt on a 200-frame clip.
| Tracker | B200 | H200 | H100 | RTX PRO 6000 | A100 80GB | A100 40GB | L40S | A10 | L4 | T4 |
|---|---|---|---|---|---|---|---|---|---|---|
| Deep OC-SORT | 104.5 | 111.4 | 101.3 | 154.9 | 62.7 | 71.8 | 72.9 | 80.2 | 74.5 | 60.3 |
| OC-SORT | 42.7 | 53.0 | 55.1 | 61.8 | 41.1 | 44.3 | 47.4 | 51.5 | 44.9 | 41.8 |
Deep OC-SORT vs OC-SORT: the four questions that decide it
Every figure below is computed from the same run as the tables above: throughput, per-frame latency, cost and track continuity for this pair specifically, rather than a general ranking.
Real-time headroom
Across the 10 tiers, Deep OC-SORT clears 30 FPS on 10 and 60 FPS on 10; OC-SORT clears 30 FPS on 10 and 60 FPS on 1. Both hold real time on every GPU tested, so this pair is decided on ID behaviour and cost rather than speed. Per frame on an NVIDIA H100 that is 9.9 ms for Deep OC-SORT and 18.1 ms for OC-SORT, detection included.
Does the ranking hold across GPUs?
Yes. Deep OC-SORT is ahead of OC-SORT on all 10 tiers, from the B200 down to the T4, so the ordering you see on an NVIDIA H100 is the ordering you will get on whatever you deploy to. That consistency is itself useful: it means this choice can be made once rather than revisited per hardware refresh.
How long an identity survives
Average track length was 80.4 frames for Deep OC-SORT and 29.6 for OC-SORT on the 200-frame clip, so Deep OC-SORT held each object for longer before losing or re-numbering it. Read alongside the fragmentation counts, that is what an ID switch feels like downstream: a counting line double-counts the same person, or a dwell-time average collapses because one visit was recorded as three. Neither number is MOTA, because this clip has no ground truth, but both come from the same run and point the same way.
Cost to run
At NVIDIA H100 rates, Deep OC-SORT costs $0.0108 per 1,000 frames against $0.0199 for OC-SORT, about 1.8× cheaper. Over a single 30 FPS camera running for an hour that is roughly $1.17 versus $2.15. That is small per camera, and a real multiplier across a wall of them. Cost here is pure occupancy: a slower tracker holds the GPU for longer, so throughput and spend are the same fact in two units.
Choosing between them
Choose Deep OC-SORT if…
Crowded or occluded scenes where identity persistence matters.
Strengths
- Strong ID stability from appearance Re-ID
- Fast on Hopper/Blackwell GPUs
- Good occlusion recovery
Trade-offs
- Re-ID model adds compute and memory
- Slower than pure-motion trackers on budget GPUs
Motion + Re-ID, 2023. Enable it with tracker="deepocsort.yaml".
Choose OC-SORT if…
Simple, sparse scenes with little occlusion.
Strengths
- No Re-ID model needed
- Simple and lightweight
- Solid motion baseline
Trade-offs
- Many ID switches / fragmentations here
- Weak through occlusion
Motion only, 2023. Enable it with tracker="ocsort.yaml".
Other head-to-head comparisons
More matchups involving Deep OC-SORT and OC-SORT, each with the same speed, cost and ID-stability breakdown.
How these numbers were measured
Deep OC-SORT and OC-SORT ran on the identical 200-frame clip with the same yolo26n.pt detector on each of the 10 GPU tiers, so the only variable is the tracker. There is no MOT ground truth on this clip, so no MOTA or IDF1 is claimed; the stability figures are raw counts. Full methodology and the benchmark script live on the hub, alongside all six trackers.
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Frequently asked questions
- Is Deep OC-SORT faster than OC-SORT?
- On an NVIDIA H100 with yolo26n.pt, Deep OC-SORT ran at 101 FPS and OC-SORT at 55 FPS end to end, detection included. Across all 10 GPU tiers Deep OC-SORT was ahead on 10 and OC-SORT on 0. The ordering is the same on every tier tested.
- Which holds object IDs better, Deep OC-SORT or OC-SORT?
- Deep OC-SORT. On the same clip it recorded 42 ID fragmentations against 113, across 12 unique IDs for Deep OC-SORT and 79 for OC-SORT, with average track lengths of 80.4 and 29.6 frames. ID stability is a property of the algorithm rather than the GPU, so this holds on any hardware.
- Is Deep OC-SORT or OC-SORT cheaper to run?
- Deep OC-SORT, at $0.0108 per 1,000 frames on an NVIDIA H100 versus $0.0199. The difference is occupancy: the slower tracker holds the GPU longer per frame, so the cost gap tracks the speed gap.
- Can Deep OC-SORT and OC-SORT run in real time?
- Deep OC-SORT sustained 30 FPS or better on 10 of the 10 GPU tiers and OC-SORT on 10. Per frame on an NVIDIA H100 that is 9.9 ms and 18.1 ms respectively. Anything under 33 ms per frame keeps up with a 30 FPS camera.
- Should I choose Deep OC-SORT or OC-SORT?
- Choose Deep OC-SORT for crowded or occluded scenes where identity persistence matters. Choose OC-SORT for simple, sparse scenes with little occlusion. OC-SORT plus a Re-ID model for stable identities. Pure motion: fast, but ID-hungry on this clip.
- Does a more expensive GPU make tracking more accurate?
- No. A faster GPU only makes tracking run faster; it does not change how accurately the tracker follows objects. Accuracy and ID-stability depend on the tracking algorithm and your detector, not the hardware. That is why this page reports speed per GPU, but ID-stability only once.
- How was this YOLO tracker benchmark run?
- Every tracker ran on the same 200-frame clip with the same yolo26n.pt detector, on each of the 10 GPU tiers. FPS is the end-to-end detection-plus-tracking rate. All six trackers are built into Ultralytics, so results are reproducible with a single script.