Cheapest Model Finder
3 questions → the cheapest model for your job
Skip spreadsheet-comparing 25 models. Tell us what you're building - we'll return the cheapest 3 that fit.
Pricing verified: 2026-06-05
Takes 30 seconds
What this calculator does
Use-case-driven model picker: tell it what you're building, get a ranked list of cheapest models meeting your quality floor — with cache + batch savings factored in.
Why use it
- Lowest sticker price isn't always cheapest in production — cache hit rate, batch eligibility, modality matter
- Use-case presets encode the actual workload (token shape, capability needs) so cheap-looking models that fail your task get auto-excluded
- Per-model "why this works" reasons make the recommendation defensible to engineering and finance
- Tier-1 / vision / agent constraints lock out models that fail compliance or capability requirements
Who uses this:
Vibe Coder
High
Quickest answer to "which is cheapest for my use case" — no manual price comparison
Small Business
High
Defensible cheap-model choice with reasons that hold up to "why this and not that"
Enterprise
Medium
Useful first pass; final selection often needs vendor-specific eval and compliance review
These are the inputs, outputs, and how you can use this calculator for your AI workloads.
📥 Inputs you provide
- What are you buildingSets capability bar + token shape
- Tier-1 provider onlyAllowlist for regulated workloads
- Vision requiredImage-capable models only
- Agent-capable requiredTool-use + reasoning required
📤 Outputs you get
- Cheapest-first model rankingTop = cheapest meeting your bar
- Per-model rationalesReasons specific to your use case
- Per-call cost at typical shapeDollar cost at use-case token shape
🎯 Use your results to
💰
Cheapest valid model in 30 seconds
Stop manual vendor-page comparison
🛡️
Quality floor stays defended
Use-case selection enforces minimum capabilities
🧾
Defensible rationale per pick
Each recommendation comes with workload-specific reasons
⚡
Catch caching + batch savings
Effective prices factor in cache and batch discounts where supported
👇 Now try the calculator below with your own AI workloads
1
Pick the right use case
Chatbot = short turns, 500/300 tokens, no special caps. Classification = 300/50 tokens, super cheap models OK. RAG = 3.5K/800 tokens, needs long-context capability. Agent = 2K/1.5K tokens, needs tool-use + reasoning. Coding = 2K/1.5K, needs coding-tuned model. Content = 1.5K/2K, longer outputs. Picking accurately matters — wrong use case = wrong cheapest answer.
2
Add constraints that are NON-negotiable
Tier-1 only = OpenAI / Anthropic / Google (excludes DeepSeek, xAI, others for regulated workloads). Vision = must handle images. Agent-capable = excludes Nano-tier and Flash-Lite which lack tool-use reasoning. Add constraints only when actually required — over-constraining hides cheap valid options.
3
Read "why this works" reasons
Top result is cheapest. Each model has reasons explaining the pick: "Cheapest Tier-1 model in 2026", "Free tier with reduced quota available", "Prompt caching 90% off — huge for repeat-context RAG", "Batch API (50% off) available — your workload is often batch-eligible". These are NOT marketing — they're workload-specific rationales.
4
Validate then ship
Before committing: (1) run the cheap-tier candidate on an eval set — does it actually meet your quality bar? (2) verify cached pricing / batch eligibility applies to your traffic pattern. (3) check vendor compliance — data residency, BAA, retention. If the cheapest fails eval, work up the list. Most teams find the 2nd-cheapest is the real winner.
📊 Calculator at a glance
🎛 CALCULATOR
1 What are you building?Determines minimum-quality bar AND the typical token shape (input/output sizes) the recommendation is costed against.How to choose: Pick the closest match to YOUR primary use case. If you have multiple use cases, run the calc once per use case — they often select different optimal models.Read the full guide →
This sets the minimum capability bar.
2 How much volume?
Daily requests at steady state.
3 Any constraints?When checked, limits to OpenAI / Anthropic / Google. Excludes DeepSeek, xAI, Mistral, and others that may not have your required compliance posture.How to choose: Check this only if you have an actual constraint (data residency rule, BAA requirement, procurement allowlist). Otherwise leave unchecked — Tier-1 models are typically 2-10× more expensive than the absolute cheapest.Read the full guide →
Compliance, region, provider trust. Pick all that apply.
📈 RESULTS
🏆 Your top 3 cheapest matches
-
📋 What now?
- Switch to the cheapest eligible tier — same capability bar, lower bill
- Open the winner in the calculator — confirm the exact monthly cost for your volume
- Keep a quality floor — your constraints already excluded anything too weak
Want a second opinion on the switch?
💼 Talk to a CloudIntelligence advisor →
Now that you have your ranked list…
What this means + what to do next
💡 What to consider beyond this ranked list for full TCO
- Quality variance at YOUR task — sticker price tells you nothing about how the model performs on your prompts
- Migration cost — switching to a new vendor often means weeks of prompt re-engineering and re-eval
- Volume commitments — some vendors' enterprise pricing beats list price 30-50% at scale
- Latency requirements — cheapest model may not meet your p95 latency SLA
Rule of thumb: Cheapest meeting your QUALITY bar (not just capability bar). Always run an eval on 50-100 representative tasks before committing.
Quantify the hidden costs:
- Get exact $/month at your real token shape (not the use-case default) Cost Calculator
- If your workload has repeat context, caching savings often dwarf model-swap savings Prompt Cache Roi
- Cheapest-from-new-vendor often comes with lock-in cost — quantify it Vendor Concentration Risk
$ How this fits your overall ROI
Picking the cheapest valid model is half the work. The other half:
- Does the cheapest model meet our quality bar on 100 real production examples?
- What's the eval and migration cost if we switch from current vendor?
- Will volume discounts from current vendor beat list-price savings from new one?
Bridge to ROI:
- Rather than one cheap model, route easy queries cheap and hard queries premium Multi Model Router
- Cache savings often beat model-swap savings on repeat-context workloads Prompt Cache Roi
- Async-eligible portion of traffic gets 50% off — often bigger than the cheap-model gap Batch Vs Realtime
Doing something different?
If picking the cheapest isn't your real question:
- You want to browse + filter, not get a single recommendation Ai Model Finder
- Your traffic is mixed — easy and hard queries should use different models Multi Model Router
- You've already picked a model and just want the dollar number Cost Calculator