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19 articles
Articles
August 20, 2026
DeepSeek-V4-Flash: specs, benchmarks, and how to run it
DeepSeek-V4-Flash is a 284-billion parameter MoE model offering agentic reasoning across a 1-million token context window. Lyceum serves it via an OpenAI-compatible API from eu-north1 in the European Union, optimized for enterprise inference at $0.15 per million input tokens.
August 12, 2026
Where to Run Kimi Models in Europe: K2.6, K2.7 Code and K3
Moonshot AI's Kimi models deliver frontier capabilities for agentic coding. K2.6 and K2.7 Code offer 1T-parameter scale with 256K context, while K3 pushes to 2.8T parameters and a 1M-token window. European teams can run them via EU-hosted APIs to maintain data residency.
July 31, 2026
DeepSeek V4 Flash: 1M-Token Context for AI Products
DeepSeek V4 Flash introduces a 284B parameter MoE architecture with 13B active parameters, delivering low time-to-first-token latency and a 1,048,576-token context window. For AI-native products, this means high-throughput agent loops and long-context retrieval hosted natively in Europe
July 31, 2026
Kimi K3 API: Where to Run It, and What a 1M-Token Context Costs
Kimi K3 offers a 1M-token context window at $3.00 input and $15.00 output per million tokens. Deploying it on Lyceum in Europe provides GDPR compliance, zero data retention, and prompt caching at $0.75 per million tokens.
June 27, 2026
GLM-5.2: specs, benchmarks, and how to run it on Lyceum
GLM-5.2 delivers a solid 1M-token context and frontier-level coding performance at a fraction of the cost. Deploy it on European infrastructure via our Serverless Inference API.
June 26, 2026
Qwen3-32B: specs, benchmarks, and how to run it on Lyceum
Qwen3-32B introduces a dual-mode architecture that smoothly switches between complex logical reasoning and efficient general-purpose chat. Now available on Lyceum's EU-hosted infrastructure, it offers a highly capable alternative to larger 70B+ models.
June 26, 2026
Qwen3.5-397B-A17B: specs, benchmarks, and how to run it on Lyceum
Qwen3.5-397B-A17B combines a massive 397-billion parameter knowledge base with an efficient 17B active-parameter routing. It delivers frontier-level coding and multimodal reasoning at a fraction of the compute cost.
June 25, 2026
Qwen3-235B-A22B: specs, benchmarks, and how to run it on Lyceum
Qwen3-235B-A22B-Instruct-2507 is Alibaba's flagship Mixture-of-Experts model, activating only 22B parameters per token for efficient performance. With a 256K context window and strong coding capabilities, it rivals top-tier proprietary models.
June 25, 2026
Qwen3-30B-A3B: specs, benchmarks, and how to run it on Lyceum
Qwen3-30B-A3B activates only 3 billion parameters per token, delivering the reasoning capabilities of a 30B model at high speeds. Learn how to deploy this cost-efficient MoE model on Lyceum's EU-sovereign infrastructure.
June 23, 2026
Nemotron-3-Super-120b-a12b: specs, benchmarks, and how to run it on Lyceum
Nemotron-3-Super-120b-a12b delivers 120B-parameter reasoning with the inference cost of a 12B model. Built on a hybrid Mamba-Transformer architecture, it excels at multi-agent workflows and long-context tasks.
June 22, 2026
Nemotron-3-Nano-30B: specs, benchmarks, and how to run it on Lyceum
NVIDIA's Nemotron-3-Nano-30B-A3B combines a Mamba-Transformer architecture with a Mixture-of-Experts design to deliver top-tier reasoning at a fraction of the compute cost. Here is how to deploy it on Lyceum's EU-sovereign infrastructure.
June 20, 2026
Llama-3.3-70B: specs, benchmarks, and how to run it on Lyceum
Llama-3.3-70B-Instruct is a text-only refresh that delivers state-of-the-art performance in reasoning, math, and coding. It matches the capabilities of much larger models while maintaining the efficiency of a 70B parameter architecture.
June 19, 2026
Hermes-4-70B: specs, benchmarks, and how to run it on Lyceum
Hermes-4-70B introduces a hybrid reasoning mode and strict JSON schema adherence for complex logic tasks. Learn how to deploy it using Lyceum's OpenAI-compatible API with GDPR-compliant processing in European data centres.
June 18, 2026
gpt-oss-120b: specs, benchmarks, and how to run it on Lyceum
gpt-oss-120b brings OpenAI's reasoning capabilities to the open-source ecosystem. With 117B parameters and a sparse MoE architecture, it delivers o4-mini-level performance while fitting on a single 80GB GPU.
June 18, 2026
Hermes-4-405B: specs, benchmarks, and how to run it on Lyceum
Hermes-4-405B introduces a hybrid reasoning mode that balances fast responses with deep, think-tag deliberation. Now available on Lyceum's European infrastructure, it delivers strong math and coding performance without the censorship of proprietary models.
June 17, 2026
GLM-5.1: specs, benchmarks, and how to run it on Lyceum
GLM-5.1 is a Mixture-of-Experts model with 754B parameters and 40B active per token, built for sustained, multi-step software engineering tasks. With a leading SWE-Bench Pro score among the models on its own card, it offers an open-weight alternative to frontier proprietary models.
May 29, 2026
Deploying Microsoft Phi-4 Inference on GPU Cloud: A Production Guide
Microsoft's Phi-4 delivers advanced reasoning at a fraction of the size of frontier models. Moving from local testing to production inference requires strict memory management and the right infrastructure stack.
May 29, 2026
Deploy Qwen 2.5 72B on GPU Cloud: VRAM Sizing and vLLM Setup
Running Qwen 2.5 72B in production requires strict memory management and the right infrastructure. Learn how to calculate VRAM requirements, configure vLLM, and deploy on EU-sovereign GPUs without hyperscaler price premiums.
May 28, 2026
Deploy Gemma 3 on European GPU Cloud: VRAM, Setup, and GDPR Compliance
Google's Gemma 3 models bring multimodal capabilities and 128K context windows to open weights AI. Running them in production requires careful VRAM planning and infrastructure that guarantees data residency.