AI Infrastructure Advisor
Describe your use case and constraints. Get ranked good-fit architectures — real models, real providers, real monthly costs — optimized for cost, latency or quality.
Live pricing across 291 curated models · data refreshed Jun 1, 2026.
Llama 3.2 1b Instruct
- • Self-host Llama 3.2 1b Instruct on 1× RTX 3090 (~2 GB).
- • ~$161/mo dedicated · est. 457 tok/s decode.
- • Scored for RAG Q&A (interactive): cost 92 · latency 95 · quality 68.
Llama 3.1 8B
- • Cerebras serves Llama 3.1 8B as a managed API — no infra to run.
- • ~$390/mo at your volume · $0.10/M tokens blended.
- • Scored for RAG Q&A (interactive): cost 80 · latency 97 · quality 71.
⚠ Data leaves your boundary — verify the provider DPA/compliance.
- CerebrasAPIfastcheapest$390/moTry
Qwen3 30B A3B
- • Self-host Qwen3 30B A3B on 2× RTX 3090 (~36 GB, tensor parallel).
- • ~$321/mo dedicated · est. 340 tok/s decode.
- • Scored for RAG Q&A (interactive): cost 83 · latency 83 · quality 77.
⚠ MoE: all experts occupy memory even though only some compute.
Llama 3.1 8B
- • DeepInfra is the cheapest of 2 providers serving Llama 3.1 8B — full price stack below.
- • ~$84/mo at your volume · $0.02/M tokens blended.
- • Scored for RAG Q&A (interactive): cost 100 · latency 75 · quality 71.
⚠ Data leaves your boundary — verify the provider DPA/compliance. Listed cost is per-token list price; committed-use, batch and enterprise contracts differ.
Qwen2.5 7B Instruct
- • SiliconFlow is the cheapest of 3 providers serving Qwen2.5 7B Instruct — full price stack below.
- • ~$195/mo at your volume · $0.05/M tokens blended.
- • Scored for RAG Q&A (interactive): cost 89 · latency 75 · quality 78.
⚠ Data leaves your boundary — verify the provider DPA/compliance. Listed cost is per-token list price; committed-use, batch and enterprise contracts differ.
GPT OSS 20B
- • Self-host GPT OSS 20B on 2× RTX 3090 (~24 GB, tensor parallel).
- • ~$321/mo dedicated · est. 312 tok/s decode.
- • Scored for RAG Q&A (interactive): cost 83 · latency 83 · quality 76.
⚠ MoE: all experts occupy memory even though only some compute.
THUDM/GLM-4-9B-0414
- • SiliconFlow serves THUDM/GLM-4-9B-0414 as a managed API — no infra to run.
- • ~$335/mo at your volume · $0.09/M tokens blended.
- • Scored for RAG Q&A (interactive): cost 82 · latency 72 · quality 82.
⚠ Data leaves your boundary — verify the provider DPA/compliance.
- SiliconFlowAPImediumcheapest$335/moTry
GPT OSS 120B
- • DeepInfra is the cheapest of 10 providers serving GPT OSS 120B — full price stack below.
- • ~$309/mo at your volume · $0.08/M tokens blended.
- • Scored for RAG Q&A (interactive): cost 83 · latency 99 · quality 61.
⚠ Data leaves your boundary — verify the provider DPA/compliance. Reasoning model: extra reasoning tokens raise real cost and latency. Listed cost is per-token list price; committed-use, batch and enterprise contracts differ.
Step 3.5 Flash
- • SiliconFlow serves Step 3.5 Flash as a managed API — no infra to run.
- • ~$510/mo at your volume · $0.13/M tokens blended.
- • Scored for RAG Q&A (interactive): cost 77 · latency 93 · quality 68.
⚠ Data leaves your boundary — verify the provider DPA/compliance. Reasoning model: extra reasoning tokens raise real cost and latency.
- SiliconFlowAPImediumcheapest$510/moTry
Claude Opus 4.8
- • Google Vertex is the cheapest of 3 providers serving Claude Opus 4.8 — full price stack below.
- • ~$31.5k/mo at your volume · $8.08/M tokens blended.
- • Scored for RAG Q&A (interactive): cost 24 · latency 35 · quality 96.
⚠ Data leaves your boundary — verify the provider DPA/compliance. Reasoning model: extra reasoning tokens raise real cost and latency. Listed cost is per-token list price; committed-use, batch and enterprise contracts differ.
Disclosure: some managed-provider links are affiliate links. Ranking is driven only by your inputs and real numbers — never by who pays. A provider appears only when it fits.
How it works
The Advisor turns the AI infrastructure decision into an explicit tradeoff. You can't maximize cost, latency and quality at once — so you pick what to optimize for, and the engine ranks every viable model and deployment against your real volume.
Managed-API options price out against live per-token rates from the providers that actually serve each open model. Self-host options compute the VRAM fit, pick the smallest GPU that works, and estimate dedicated cloud cost and decode throughput. If your data must stay in-house, managed options are removed automatically.
Frequently asked questions
How does the Advisor decide what to recommend?
Every candidate model + deployment gets an HH Score — a transparent blend of quality, price-performance and latency, weighted by what you optimize for. By default it leads with quality, so a cheap-but-weak model never wins automatically. Cost is computed from real per-token pricing (models.dev) or real cloud GPU pricing; quality is anchored to public benchmarks (LMArena Elo, Artificial Analysis). Full method and sources at /methodology.
Where does the data come from?
We advertise every source openly. Pricing + provider availability: models.dev. Quality/performance: LMArena Chatbot Arena Elo and Artificial Analysis. Architecture (params, layers, KV) for VRAM math: HuggingFace model configs. GPU specs: vendor sheets + TechPowerUp; GPU $/hr: RunPod, Vast.ai, Lambda. See /methodology for the full list and refresh cadence.
Why show both managed and self-host options?
Because the right answer depends on your constraints. If data must stay in your boundary, only self-host is shown. Otherwise you see both, ranked by your priorities, so you can compare total cost honestly.
Are the costs exact?
They are first-order estimates within ~10–20%, based on real prices and your stated volume. Throughput and VRAM use standard GQA formulas. Always validate with a real benchmark before committing — every self-host recommendation links a reproducible config.
How do you make money, and does it bias recommendations?
Some managed providers may carry referral links, always disclosed. Ranking is driven only by your optimize-for choice and real numbers — never by who pays. A provider appears only when it is genuinely a good fit.