Monsder guide
How to choose an AI server
Start with the task, model and measurable workload requirements. Estimate memory, determine the GPU configuration, then validate the complete server: CPU, RAM, storage, interconnects, power and cooling. Compare budgets after engineering suitability.
Prepare the workload requirements
Describe the task: document question answering, content generation, speech recognition or another workload. Record inference, fine-tuning or training, model version, precision, context, concurrent requests and required response time. Image, video and audio workloads need modality-specific parameters.
Separate requirements from assumptions. For example, 20 concurrent requests is a workload requirement; one GPU delivering the required speed is a hypothesis until measured. If no model is selected, first compare candidates against the task and known architecture details.
Validate the complete configuration
VRAM estimation answers only part of the question. System RAM, space for models and data, CPU and storage also matter. Multiple accelerators require a supported model distribution method, appropriate interconnects and platform validation. Memory on separate GPUs is not automatically a shared pool.
Check form factor, slot count and placement, connectors, power headroom, cooling and deployment conditions. Monsder selects new equipment and excludes used or refurbished hardware. A reference configuration still requires confirmation of compatibility, availability and delivery capability.
From an estimate to an engineering decision
Start with a guest calculation in Monsder and retain the selected inputs and unknowns. An account is required to save a server-side project and request an engineer review. Automated results are preliminary; the final engineering decision and commercial proposal go through specialist review.
Price and availability do not change the calculation engine. A missing price does not exclude an engineering candidate. Performance and reliability require tests in the selected environment; services are added separately when delivery capability is confirmed.
Common questions
Can I choose a server by VRAM alone?
No. VRAM is one constraint. Validate the runtime, complete platform, power and cooling, and measure performance under the specified load.
Is a calculation a commercial quotation?
No. It is a preliminary engineering estimate. The final decision and commercial quotation require specialist review.
Sources and scope
Primary documentation explains memory and runtime principles. The Monsder workflow describes the current preliminary calculator. Examples are not GPU benchmarks; final engineering decisions require specialist review.
Apply the method
- How much VRAM does an LLM need?
Estimate LLM memory from weights, quantization, KV cache, context and concurrency. An 8B example and the limits of a preliminary Monsder calculation.
- Which models fit your GPU?
Match an LLM to your GPU using available VRAM, quantization, context and concurrency. Why fitting in memory does not establish a validated deployment.