Overall Winner: Silo AI·60/ 100
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Silo AIWinner
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Silo AI vs StepFun

In-depth comparison — valuation, funding, investors, founders & more

Winner
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Silo AI

🇫🇮 Finland · Peter Sarlin

AcquiredFoundation ModelsEst. 2017

Valuation

N/A

Total Funding

$60M

60
Awaira Score60/100

100-500 employees

Full Silo AI Profile →
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StepFun

🇨🇳 China · Jiang Daxin

Series AFoundation ModelsEst. 2023

Valuation

N/A

Total Funding

$200M

58
Awaira Score58/100

100-500 employees

Full StepFun Profile →
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Analyst Summary

Generated from real data · No AI hallucinations

Both Silo AI and StepFun compete directly in the Foundation Models space, making this a head-to-head matchup within the same market segment. Silo AI operated as a private European AI lab providing foundation model development, applied AI research, and AI product engineering services to enterprise clients across Europe, building custom AI systems and adapting open-source foundation models for domain-specific applications in manufacturing, healthcare, and financial services. StepFun develops multimodal foundation models for Chinese and English language applications, producing the Step series of large language and vision-language models that target enterprise deployment through API and private cloud licensing.

Neither company has publicly disclosed a valuation at this time. On the funding side, StepFun has raised $200M in total — $140M more than Silo AI's $60M.

Silo AI has 6 years more market experience, having been founded in 2017 compared to StepFun's 2023 founding. In terms of growth stage, Silo AI is at Acquired while StepFun is at Series A — a meaningful difference for investors evaluating risk and upside.

Silo AI operates out of 🇫🇮 Finland while StepFun is based in 🇨🇳 China, giving each a distinct home-market advantage. On Awaira's 0–100 composite score, both companies are closely matched — Silo AI scores 60 and StepFun scores 58.

Metrics Comparison

MetricSilo AIStepFun
💰Valuation
N/A
N/A
📈Total Funding
$60M
$200MWINS
📅Founded
2017
2023WINS
🚀Stage
Acquired
Series A
👥Employees
100-500
100-500
🌍Country
Finland
China
🏷️Category
Foundation Models
Foundation Models
Awaira Score
60WINS
58

Key Differences

📈

Funding gap: StepFun has raised $140M more ($200M vs $60M)

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Market experience: Silo AI has 6 years more (founded 2017 vs 2023)

🚀

Growth stage: Silo AI is at Acquired vs StepFun at Series A

🌍

Market base: 🇫🇮 Silo AI (Finland) vs 🇨🇳 StepFun (China)

⚔️

Direct competitors: Both operate in the Foundation Models market segment

Awaira Score: Silo AI scores 60/100 vs StepFun's 58/100

Which Should You Choose?

Use these signals to make the right call

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Choose Silo AI if…

Top Pick
  • Higher Awaira Score — 60/100 vs 58/100
  • More market experience — founded in 2017
  • Finland-based for regional compliance or proximity
  • Silo AI operated as a private European AI lab providing foundation model development, applied AI research, and AI product engineering services to enterprise clients across Europe, building custom AI systems and adapting open-source foundation models for domain-specific applications in manufacturing, healthcare, and financial services
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Choose StepFun if…

  • Stronger investor backing — raised $200M
  • China-based for regional compliance or proximity
  • StepFun develops multimodal foundation models for Chinese and English language applications, producing the Step series of large language and vision-language models that target enterprise deployment through API and private cloud licensing

Users Also Compare

FAQ — Silo AI vs StepFun

Is Silo AI bigger than StepFun?
Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Silo AI employs 100-500 people, while StepFun has 100-500 employees.
Which company raised more funding — Silo AI or StepFun?
StepFun has raised more in total funding at $200M, compared to Silo AI's $60M — a gap of $140M.
Which company has a higher Awaira Score?
Silo AI holds the higher Awaira Score at 60/100, compared to StepFun's 58/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 2-point gap that reflects meaningful differences in scale or traction.
Who founded Silo AI vs StepFun?
Silo AI was founded by Peter Sarlin in 2017. StepFun was founded by Jiang Daxin in 2023. Visit each company's profile on Awaira for a full founder biography.
What does Silo AI do vs StepFun?
Silo AI: Silo AI operated as a private European AI lab providing foundation model development, applied AI research, and AI product engineering services to enterprise clients across Europe, building custom AI systems and adapting open-source foundation models for domain-specific applications in manufacturing, healthcare, and financial services. The Helsinki company combined academic research partnerships with commercial AI deployment expertise.\n\nThe company raised approximately $60 million in venture funding before being acquired by AMD in July 2024 for approximately $665 million, one of the largest acquisitions of a European AI company. The acquisition gave AMD an AI software engineering team to develop AI software and tools optimised for AMD Instinct GPU hardware, addressing the critical software ecosystem gap that AMD faces in competing against NVIDIA CUDA in the AI training and inference market.\n\nSilo AI competed in the European AI services and research market alongside AI labs and consultancies, but its acquisition by AMD represented a strategic uplift from commercial AI services to chip ecosystem development. The acquisition price reflected AMD valuation of Silo AI engineering talent and AI model optimisation expertise rather than its revenue run rate, indicating the premium that semiconductor companies are willing to pay to close software ecosystem gaps against NVIDIA dominance. Post-acquisition, the Silo AI team focuses on optimising AI frameworks, model libraries, and developer tools for AMD AI accelerator hardware. StepFun: StepFun develops multimodal foundation models for Chinese and English language applications, producing the Step series of large language and vision-language models that target enterprise deployment through API and private cloud licensing. The Beijing company was founded by Jiang Daxin, a former senior executive at Baidu, bringing search and large-scale AI infrastructure experience to foundation model development in the rapidly competitive Chinese LLM startup market.\n\nThe company raised approximately $200 million in early funding from Chinese venture capital firms including Hillhouse Capital and other technology-focused investors backing the wave of Chinese foundation model startups that emerged following the launch of ChatGPT. StepFun models are positioned for enterprise customers in finance, legal, and customer service sectors requiring high-quality Chinese language reasoning and instruction following capabilities.\n\nStepFun competes in a crowded Chinese foundation model market alongside Moonshot AI, MiniMax, Zhipu AI, and Baichuan, as well as the AI divisions of Alibaba, Baidu, and ByteDance that have substantially greater compute resources and distribution. The Chinese foundation model market has seen aggressive fundraising and model release activity as the government signals support for domestic AI capability development. Differentiation among Chinese LLM startups is increasingly difficult as model benchmark performance converges, shifting competition toward vertical domain adaptation, inference cost, and enterprise integration services.
Which company was founded first?
Silo AI was founded first in 2017, giving it 6 years of additional market experience. StepFun was founded later in 2023. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.
Which company has more employees?
Both Silo AI and StepFun report similar employee counts of approximately 100-500. Team size is often a proxy for operational scale, though lean AI companies can punch well above their headcount.
Are Silo AI and StepFun competitors?
Yes, Silo AI and StepFun are direct competitors — both operate in the Foundation Models space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.