Baseten
Circuit mix
Where Baseten shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- AI engineering & MLOps67%11 events
- Cloud providers23%4 events
- Research7%1 event
- Software engineering & trading tech3%1 event
Presence by conference and year
Each cell is one conference in one year. Fill shows the company sponsored, shaded by its best tier that year; a dot means it had speakers there. Hover for details; click to open the event.
- Title
- Platinum
- Gold
- Silver
- Bronze
- Other / unlabeled tier
- Had speakers
Activity by year
Three measures on one year axis; each panel has its own scale. 2027, 2028 is still mostly ahead, so its bars are faded and incomplete.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
Distinct speakers
People from this company on a program that year, each counted once.
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Title
- Platinum
- Gold
- Silver
- Bronze
- Other / unlabeled
Where they've grown or pulled back
UpSponsored 4 conferences in 2026, up from 3 in 2024.
Counted per conference. 2026 is the latest year whose conferences have mostly happened. Tiers use the best tier each year; swatches show the path, oldest first. A conference counts as pulled out only when a later event published a complete sponsor list, since most events don’t say whether their list is complete.
New 3
First sponsored in 2025 or later.
- Google Cloud Nextfirst sponsored 2026, Bronze
- NeurIPS (Conference on Neural Information Processing Systems)first sponsored 2026, Title
- ODSC (Open Data Science Conference)first sponsored 2025, tier not listed
Moved up 1
Best tier rose between the first and latest year with a ranked tier.
- PyTorch ConferenceSilver 2024 → Platinum 2026
Steady 2
Sponsored in most years of its span at the same tier.
- AI Engineer (World's Fair, Summit and regional editions)every year 2024–26, mostly Gold
- AWS re:Inventevery year 2024–25, Gold
Lookalikes
Companies with the most similar conference footprint: they sponsor and speak at the same conferences. Bars are cosine similarity, from 0 (nothing shared) to 1 (identical).
- Luma AI0.82
- Parasail0.81
- FriendliAI0.80
- Together AI0.79
- poolside0.78
- ElevenLabs0.78
- PromptQL0.75
- Prime Intellect0.73
1 Cluster: AI Engineer · MLOps World circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 13 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| NVIDIA | 9 | 69% |
| Amazon Web Services | 8 | 62% |
| Datadog | 8 | 62% |
| 8 | 62% | |
| Weights & Biases | 8 | 62% |
| AMD | 7 | 54% |
| Databricks | 7 | 54% |
| Elastic | 7 | 54% |
| IBM | 7 | 54% |
| Intel | 7 | 54% |
| Microsoft | 7 | 54% |
| Neo4j | 7 | 54% |
| Arize AI | 6 | 46% |
| Atlassian | 6 | 46% |
| Oracle | 6 | 46% |
Neighborhood: companies with nearby conference footprints
Baseten (ringed) and the 30 companies closest to it on the company map. Close together means they sponsor and speak at many of the same conferences. Distances are only meaningful locally; the axes have no meaning. Dot size: conferences present at. Color: cluster.
Sponsorships 13
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| NeurIPS 2026 (Sydney) | Dec 6–12, 2026 | Sydney, Australia | Diamond | Title |
| AI Engineer Code Summit 2026 | Nov 10–12, 2026 | San Francisco, United States | SUPPORTING PARTNERS | Other |
| PyTorch Conference North America 2026 | Oct 20–21, 2026 | San Jose, United States | Platinum | Platinum |
| AI Engineer World's Fair 2026 | Jun 29, 2026 – Jul 2, 2026 | San Francisco, United States | Gold | Gold |
| Google Cloud Next '26 | Apr 22–24, 2026 | Las Vegas, United States | Velocity | Bronze |
| AWS re:Invent 2025 | Dec 1–5, 2025 | Las Vegas, United States | Gold | Gold |
| ODSC AI West 2025 | Oct 28–30, 2025 | Burlingame, United States | Partner (untiered) | Unlabeled |
| PyTorch Conference 2025 | Oct 22–23, 2025 | San Francisco, United States | Platinum | Platinum |
| AI Engineer World's Fair 2025 | Jun 3–5, 2025 | San Francisco, United States | Gold Sponsors | Gold |
| AI Engineer Summit 2025 (New York) | Feb 19–22, 2025 | New York, United States | Gold Sponsors | Gold |
| AWS re:Invent 2024 | Dec 2–6, 2024 | Las Vegas, United States | Gold | Gold |
| PyTorch Conference 2024 | Sep 18–19, 2024 | San Francisco, United States | Silver | Silver |
| AI Engineer World's Fair 2024 | Jun 25–27, 2024 | San Francisco, United States | Supporters | Other |
Speakers 18
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Francisco Javier Arceo | QCon AI New York 2026 | speaker | Open Source Agentic Inference: Unlocking the Harness with vLLM | — |
| Ian Carrasco | QCon AI New York 2026 | speaker | From Speech Models to Voice Agents | — |
| Lei Pan | QCon AI New York 2026 | speaker | From Speech Models to Voice Agents | — |
| Colin McGrath | AWS re:Invent 2026 | breakout | Scaling inference compute across clusters (sponsored by Baseten) | — |
| Francisco Javier Arceo | AI Engineer Code Summit 2026 | workshop | Keep the Harness, Own Your Inference | — |
| Philip Kiely | AI Engineer Code Summit 2026 | speaker | Inference Engineering for Coding Agents | — |
| Chen Wang | AI Engineer Shanghai 2026 | speaker | Full-Stack Inference Engineering: Latency, Throughput and Cost | — |
| Philip Kiely | AI Engineer World's Fair 2026 | speaker | What's New in Inference Engineering | Video |
| Philip Kiely | AI Engineer Miami 2026 | speaker | How to quantize models (without killing quality) | — |
| Philip Kiely | AWS re:Invent 2025 | lightning talk | High-performance inference for frontier AI models (sponsored by Baseten) | Video |
| Pankaj Gupta | PyTorch Conference 2025 | speaker | Sponsor Session: Low-Precision Inference without Quality Loss: Selective Quantization and Microscaling | — |
| Philip Kiely | PyTorch Conference 2025 | speaker | Sponsor Session: Low-Precision Inference without Quality Loss: Selective Quantization and Microscaling | — |
| Amir Haghighat | AI Engineer World's Fair 2025 | speaker | The Rise of Open Models in the Enterprise | Video |
| Philip Kiely | AI Engineer World's Fair 2025 | expo session | Optimizing inference for voice models in production | Video |
| Philip Kiely | AI Engineer World's Fair 2025 | workshop | Introduction to LLM serving with SGLang | Video |
| Phil Howes | AWS re:Invent 2024 | lightning talk | Faster, cheaper, better: Optimizing inference for production AI (sponsored by Baseten) | Video |
| Pankaj Gupta | AI Engineer World's Fair 2024 | workshop | From model weights to API endpoint with TensorRT-LLM | Video |
| Philip Kiely | AI Engineer World's Fair 2024 | workshop | From model weights to API endpoint with TensorRT-LLM | Video |