Labelbox
RL data engine for frontier AI teams building foundation models and evals
If you're building frontier AI models and need RL data, custom evals, or robotics annotations at scale, Labelbox is the de facto platform. The re-enabled Starter tier lowers the barrier for smaller teams, but serious budgets are still required for enterprise-grade solutions. Not for simple image classification at low cost.
Verified 17d ago · liveness 95/100 · cite: rightaichoice.com/tools/labelbox
- AI labs building foundation models needing RL post-training data at scale
- Teams requiring custom, expert-crafted evaluations for multimodal models
- Robotics companies needing full-stack data with trajectories and video
- Organizations wanting private AGI benchmarks before public model release
- Small teams needing simple image classification labeling at low cost
- Projects that can use generic public datasets without custom data needs
- Teams without budget for enterprise-level data solutions
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Skip Labelbox if you need a simple, low-cost image classification tool or lack the budget for enterprise-scale data operations.
On-demand labeling services add significant cost and require contract negotiation.
The free Starter tier (re-enabled June 2026) supports basic labeling for small teams, but enterprise features require contacting sales, making it hard to compare costs. For simple needs, dedicated labeling tools like Supervisely may be cheaper; for frontier research, Labelbox is unmatched.
In short
Labelbox — RL data engine for frontier AI teams building foundation models and evals. Best for AI labs building foundation models needing RL post-training data at scale, Teams requiring custom, expert-crafted evaluations for multimodal models, Robotics companies needing full-stack data with trajectories and video. Free to use.
What's new in Labelbox
Checked 15 days agoAcross the latest 6 updates: 2 feature updates, 1 launch and 3 news mentions.
Do AI models want to be watched? Measuring monitorability disposition in large reasoning models
Research finds models rarely flag misbehavior; introduces monitorability disposition as a missing alignment property.
Introducing Recursion: The RL platform for enterprise specialist agents
Labelbox launches Recursion, a unified reinforcement learning platform for developing and deploying specialist AI models.
Where models change their minds: Identifying branchpoints for NLA training
Study explores whether NLAs can surface internal patterns behind shortcut behavior using branchpoint analysis.
Starter tier re-enabled; Opus 4.8 model added; UI color refresh; user groups up to 100K
Starter tier returns for new and existing users. Opus 4.8 available on Model tab. UI updated with warmer light mode. Max user groups increased to 100K.
When benchmarks saturate, what comes next? Meta’s GIM pushes AI evaluation toward integrated reasoning
Meta Superintelligence Labs introduces Grounded Integration Measure (GIM) benchmark for integrated reasoning.
AI critics in audio/video editors; search in document editor; multi-label without scoring; read-only predictions
AI critics now work across all classification types in audio/video. Ctrl+F search added to document editor. Multi-label projects can disable consensus scoring. Predictions can be imported as read-only.
Viability Score
How likely is Labelbox to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- RL environments for reasoning, tool use, computer use (Horizon)
- Full-stack robotics data: video, trajectories, annotations (Terra)
- Alignerr expert network: 2.6M+ domain experts across 40+ countries
- Rubric-based multimodal evaluations (text, vision, reasoning)
- Private AGI benchmarks for frontier model evals
- Head-to-head arena evals with human judgment
- Recursion platform for building and improving enterprise agents
- EchoChain audio benchmark for reasoning under pressure
- Multi-label without consensus flexible labeling
- Read-only predictions preserve human annotations
- AI critics in audio/video editors for grammar checking
- Agent Studio for enterprise agent simulation
- Opus 4.8 model integration (June 2026)
- Starter tier free (re-enabled June 2026)
- User groups up to 100K
About Labelbox
Labelbox is the reinforcement learning data engine designed for frontier AI labs and enterprises building foundation models, specialist agents, and robotics. Used by over 90% of leading U.S. AI labs, the platform provides end-to-end infrastructure for RL post-training, custom evaluations, and robotics data. Key capabilities include Horizon RL environments for reasoning, tool use, and computer use; Terra full-stack robotics data with video and trajectories; and the Alignerr expert network of 2.6M+ domain experts for real-world grounding signals. The newly launched Recursion platform (June 2026) enables enterprises to build, evaluate, and continuously improve specialist AI agents on production workflows. Unlike generic data labeling tools, Labelbox focuses on frontier AI research and post-training at scale, backed by applied research published at CVPR and NeurIPS.
Behind the Verdict
Labelbox sits at the intersection of data labeling and RL infrastructure, serving the handful of labs pushing foundation model capabilities. Its recent launch of Recursion (June 2026) extends the platform from data generation to enterprise agent training, signaling a pivot toward production deployments. The partnership with Meta on the GIM benchmark demonstrates the depth of its evaluation capabilities — this isn't a tool for casual annotation projects. The re-enabled Starter tier ($0/mo) is a welcome move for researchers and small teams who want to experiment with RL environments or small-scale evals, but the real value lies in enterprise contracts that include custom hardware for robotics, thousands of domain experts, and dedicated support. Competitors like Scale AI or Snorkel AI offer broader data program coverage, but Labelbox's focus on RL post-training and robotics (Terra) gives it an edge for frontier use cases. Where it falls short is cost and complexity: teams with simple image classification needs or limited budgets will find it overkill. Also, while the Alignerr network is vast, quality control across 2.6M+ experts can be inconsistent without rigorous rubrics, so invest in prompt engineering. For AI labs building the next generation of reasoning models, Labelbox is worth the price.
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Real-world workflow fit
Concrete scenarios for the personas Labelbox actually fits — and what changes day-one when you adopt it.
You need preference pairs for reasoning tasks. Use Labelbox's RL environment to generate prompts, collect human rankings via Alignerr, and integrate reward signals into your training pipeline.
Outcome: High-quality preference data for RLHF, improving model reasoning performance.
You have raw video and sensor data. Upload to Labelbox's Terra product, use built-in annotators to label trajectories and keyframes, then export to your training framework.
Outcome: Structured multimodal dataset ready for model training.
Use Cases
- Collect preference pairs and reward signals to fine-tune LLMs with RLHF using expert annotators
- Evaluate multimodal model performance with custom rubrics and head-to-head arena comparisons
- Generate supervised fine-tuning data for coding, science, and industry workflows from domain experts
- Create private benchmarks to assess frontier capabilities before public release
- Label video trajectories and sensor data for embodied AI and robotic manipulation
- Perform red teaming and safety evaluation to identify vulnerabilities in AI models
- Test audio models with EchoChain benchmark for real-time dual-stream reasoning
Models Under the Hood
as of 2026-07-14
Limitations
- Free tier availability and specific user/project caps are not detailed on the current site; pricing information requires contacting sales.
- On-demand labeling services via Alignerr network may add cost and require contract negotiation.
- The platform is cloud-dependent with no mention of air-gapped deployment.
- Advanced features like Foundry and AI critics may be restricted to paid tiers.
as of 2026-06-28
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Labelbox tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Starter
$0/mo
Ideal for
Small teams or individual researchers exploring RL data workflows with basic labeling and evaluation needs.
What this tier adds
Free entry point with limited throughput and storage; re-enabled June 2026.
Enterprise
Contact sales
Ideal for
Frontier AI labs and enterprises needing full RL environments, Alignerr expert access, and custom infrastructure at scale.
What this tier adds
Unlocks unlimited projects, 100K user groups, RL environments, Alignerr network, Terra robotics, Recursion, and dedicated support.
Where the pricing makes sense
The company stage and team size where Labelbox's pricing actually pencils out — and where peers do it cheaper.
The free Starter tier (re-enabled June 2026) supports basic labeling for small teams, but enterprise features require contacting sales, making it hard to compare costs. For simple needs, dedicated labeling tools like Supervisely may be cheaper; for frontier research, Labelbox is unmatched.
Setup time & first value
How long it actually takes to get something useful out of Labelbox — broken out by persona, not the marketing-page minute.
For basic labeling projects, you can be annotating within an hour using the Starter tier. RL environments and Alignerr access require enterprise setup, which may take 1-2 weeks with sales onboarding.
Switching to or from Labelbox
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Supervisely: Export projects in COCO/VOC format, then import via Labelbox's API or CSV upload.
- ↗To Supervisely: Export annotations via Labelbox's export API and map ontologies to Supervisely's format.
Integrations
Resources & Guides
- Documentationlabelbox.com
Get started with Labelbox
Labelbox accelerates the creation of high-quality, differentiated data by combining on-demand expert labeling services with the industry-leading data labeling platform.
- Guidelabelbox.com
Guides
Covering everything you need to know in order to build AI products faster.
- Resourcelabelbox.com
Customer support
How to work with Labelbox support to report issues and feedback.
- Resourcedocs.labelbox.com
Llms
Helpful link from docs.labelbox.com
- Resourcelabelbox.com
Blog
Covering everything you need to know in order to build AI products faster.
Official links
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