GPUs tool

VRAM fit checker

Check whether model size, quantization, context, batch, and adapters fit with headroom.

Fast answerA fit recommendation: buy, rent first, reduce model/context, or move to a higher-memory GPU.

Inputs

What to collect

Model size	Target parameter count and quantization level.
Context length	Expected prompt, retrieved context, and answer size.
Concurrency	Batch size, parallel users, adapters, and working buffers.

Method

How to use it

1	Start with the largest model and longest context you actually need.
2	Leave memory headroom for KV cache, adapters, drivers, and spikes.
3	Compare speed only among GPUs that fit the workload.

Output

How to read the result

Fits	Headroom remains	Proceed to power, cooling, driver, and price checks.
Borderline	Reduce context or quantization	Rent or test locally before buying.
Does not fit	Move memory tier	A faster small-memory card is the wrong purchase.

Thresholds

Useful vs risky

Healthy	Target workload leaves 15-25% VRAM headroom.
Risky	The card fits only in a demo with tiny context and one user.

Buyer tools

Quick checks before a shortlist

All 20 tools

AI Modelsai model cost calculator

AI model cost calculator

Use this before choosing a default model. The useful answer is not the cheapest token price; it is the cheapest solved task with acceptable latency and failure rate.

AI Modelsllm context window planner

LLM context window planner

Long context helps only when the model still follows instructions near the end of the prompt. This planner forces a fit check before a bigger context tier becomes the easy answer.

AI Modelsprompt routing savings estimator

Prompt routing savings estimator

Routing is useful when easy prompts are common and failure is observable. It is wasteful when every task is rare, expert, or hard to classify.

AI Modelsinference latency budget planner

Inference latency budget planner

A fast model can still feel slow if retrieval, tool calls, retries, and post-processing are not budgeted. This planner keeps the whole user path visible.

AI Modelsmodel eval sample size planner

Model eval sample size planner

Small evals can still be useful if they are realistic and repeated. This tool makes the sample deliberate: enough cases to catch regression, not so many that no one maintains it.

AI Toolsrag chunk size planner

RAG chunk size planner

Chunking is not a magic number. The right size depends on the shape of the source and whether the model needs local detail, full sections, or cross-document synthesis.

AI Toolsembedding storage cost estimator

Embedding storage cost estimator

Embedding cost is rarely just the first import. Refresh cycles, duplicate content, metadata, backups, and permission filters decide whether the system stays manageable.

AI Toolsapi rate limit planner

API rate limit planner

Rate limits are product constraints. This planner helps choose batching, backoff, queueing, and multi-model fallback before launch traffic teaches the lesson.