Turing review: a training data company built for coding and STEM data
Answer in brief: Turing is the specialist to shortlist when your LLM post-training problem is code. It sells custom and off-the-shelf datasets, benchmarks, expert contributors and RL environments across software engineering, enterprise knowledge work and STEM. It publishes named work with NVIDIA and Salesforce AI Research and reports 1,000+ deployable RL environments (a company claim). It raised a $111M Series E at a $2.2B valuation in June 2025. Pricing is custom, and dataset samples are available on request. This review is independent research from public sources.
Best-for verdict: top alternative for LLM post-training when the gap is coding. Turing grew out of a developer network, so it starts from strength in code. Visit Turing →
What Turing does for training data buyers
- Coding data: multilingual, multi-domain code data for benchmarking, fine-tuning and reinforcement, including SWE-Bench++, a private 900+ task CodeBench set, infrastructure-as-code packs and function-calling evaluations.
- RL environments: browser, desktop, tool/API and backend/MCP environments, including clones of Jira, Salesforce and Zendesk, with seed data, trajectory capture, resets and deterministic or state-tracked verifiers.
- Experts and research: a global expert network covering software, knowledge work and frontier STEM.
- Enterprise services: help deploying agentic systems.
Who it fits
Turing fits labs and model teams improving coding agents, software-engineering benchmarks or STEM reasoning, and enterprises that want agents trained on realistic clones of business apps.
Why it stands out
- Coding pedigree. A developer talent network turned into a frontier-data company.
- Named cases. 1,500+ Verilog tasks for NVIDIA's CVDP benchmark, and step-level Olympiad-math evaluation for Salesforce AI Research.
- Environment scale. Turing reports 1,000+ RL environments across 25 domains and 600+ consumer clones delivered to frontier labs (company claims).
- Frontier partners. Its site shows Anthropic, Gemini and NVIDIA among its frontier-lab relationships.
- Funding. A $111M Series E at a $2.2B valuation (June 2025), bringing total funding to $225M.
The catches
- Narrower modality focus. It is not the pick for speech or computer-vision labeling.
- Thin homepage. The homepage says little, so ask for samples and references.
- Partner logos without scope. Turing does not disclose the scope of its Anthropic and Gemini relationships.
Pricing
Custom. Request dataset samples through Turing's site.
Best alternatives to Turing
- Surge AI, our post-training winner across coding, reasoning and agentic data.
- Snorkel AI, for agentic-coding benchmarks and verifiable rewards.
- Mercor, for APEX-SWE and professional-domain evals.
Turing FAQ
Is Turing good for coding training data?
Yes. Coding is its core strength: datasets, SWE benchmarks, function-calling evaluations and coding RL environments.
How much did Turing raise?
Turing announced a $111M Series E at a $2.2B valuation in June 2025.
Does Turing offer samples?
Yes. You can request dataset samples on its site.
Sources
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