Provider Choice
Vendor evaluation of Lyceum as a provider: company stability, differentiation, trials, startup credits and how to start. Serves buyers de-risking the provider decision.
12 articles
Subclusters
Articles
1 October 2026
Together AI Alternatives for EU Data Residency
A roster of per-token providers with European processing, with the region question answered per provider and, where it matters, per model.
30 September 2026
Inference Provider Reliability: Verify Uptime Without an SLA
An SLA is a financial apology, not an engineering guarantee. Evaluate an inference provider's reliability by verifying their open-stack architecture, scrutinizing their public status page, and measuring latency metrics like TTFT and ITL yourself.
17 September 2026
Is Your Inference Provider Quantizing the Model: How to Tell
If a model behaves differently across providers, compare task quality under controlled settings. These tests cannot prove quantization; request documented serving details to understand the configuration.
18 September 2026
How AI Consultancies Choose LLM APIs for Client Projects
For AI consultancies, selecting an LLM API is about managing deal risk and reselling margins. This guide breaks down how to protect client data, avoid vendor lock-in with OpenAI SDK compatibility, and deploy EU-sovereign models to pass strict enterprise InfoSec audits.
18 September 2026
Switching the OpenAI SDK to an Open-Model Endpoint
Changing the base URL in the OpenAI SDK takes a minute, but a true migration requires checking five critical behavioural differences underneath the compatible interface. This guide covers how to repoint the SDK and verify structured output, tool calls, and ignored parameters.
21 August 2026
How to Test an Open-Weight Model for Free Before You Commit
Evaluating open-weight models on free API tiers allows teams to benchmark latency, cost, and quality without hardware capex. By pairing free trial credits with an automated evaluation harness, engineers can validate an LLM's performance on domain-specific tasks before committing.
13 August 2026
Modal vs RunPod for Serverless GPU Inference
Modal and RunPod offer leading serverless GPU platforms, but actual cost is driven by billing mechanics like idle timeouts and cold starts, not just the per-hour rate. This comparison breaks down deployment lock-in, serverless premiums, and strict EU compliance options.
12 August 2026
Groq Alternatives in Europe: Fast Inference Inside the EU
While Groq's custom LPUs deliver massive token generation speed, European teams face severe transatlantic network latency that undermines these gains. By hosting models locally on sovereign infrastructure, enterprises recover the Time to First Token gap and ensure GDPR compliance.
9 June 2026
The 2026 Guide to AI Inference SLAs: Uptime, Economics, and EU Compliance
Deloitte expects inference to take roughly two-thirds of all compute in 2026. When your application relies on sub-second LLM responses, every minute of provider downtime lands on a live user session.
9 May 2026
US-Based Inference APIs vs. EU Sovereign Providers: A Strategic Guide
When hyperscaler credits expire, infrastructure decisions shift from prototyping speed to production sustainability. Here is why relying on US-based APIs introduces severe compliance risks, and how the open-source stack has closed the performance gap.
3 May 2026
Fireworks and Baseten Alternatives in Europe: A Strategic Guide
US-based managed inference platforms offer excellent developer experiences but fail on EU data sovereignty and cost at scale. Learn how European ML teams are migrating to sovereign infrastructure to maintain compliance and reduce GPU spend.
20 April 2026
OpenAI Compatible API Self Hosted: A Guide for EU AI Teams
Relying on proprietary US-based APIs creates significant risks for European AI teams, from GDPR non-compliance to unsustainable scaling costs. By adopting a self-hosted, OpenAI-compatible architecture, you can maintain full control over your data residency while moving to per-second and per-token pricing you can model directly against your own traffic.