Is it cheaper to run a local coding LLM than pay for GitHub Copilot?

Not at August 2026 hardware prices, if you are replacing a cheap plan. GitHub Copilot Pro is $10/month. The cheapest GPU that runs a genuinely useful local coding model costs $329-460 after the 2026 memory price spike, and a 16GB card is $589-805, so payback against a $10 plan runs from 33 to 81 months before counting electricity. Against Claude Max at $100/month the math flips and the same cards pay for themselves in 3 to 8 months. The subscription tier you are replacing decides the answer, not the hardware.

What is the cheapest GPU that runs a useful local coding assistant?

An RTX 3060 12GB at $329-460 as of August 2026 is the practical floor, though Intel's Arc B580 12GB at about $300-310 is often cheaper for the same capacity. It runs 8B models at Q4_K_M with usable context and drives a local coding agent. A 16GB card is the better buy if the budget allows, because 16GB opens up 14B-class models where local coding quality becomes genuinely competitive rather than merely functional — expect $589-805 for an RTX 5060 Ti 16GB. The RTX 4060 Ti 16GB is the card this guide used to recommend at $450-500; that price is stale and we have not verified a current one.

How long until local AI hardware pays for itself vs a subscription?

Divide hardware cost by monthly subscription cost, then add electricity. At August 2026 prices, against Copilot Pro at $10/month an RTX 3060 12GB at $329-460 takes 33-46 months and a 16GB RTX 5060 Ti at $589-805 takes 59-81 months. Against Claude Pro at $20/month those become 16-23 and 29-40 months. Against Copilot Max or Claude Max at $100/month they become 3-5 and 6-8 months. Electricity pushes every figure out further: the US residential average is now about $0.18/kWh, so a GPU drawing 300W around the clock adds roughly $39/month, which against a $10 or $20 plan means the local setup can cost more per month to run than the subscription it replaced.

Can a local model actually replace Claude Code or Copilot?

For narrow, repetitive, high-volume work, yes. For hard multi-file reasoning, frontier models still lead. The realistic pattern most people land on is hybrid routing: repetitive and privacy-sensitive work goes local, hard problems escalate to a frontier model. That means you often do not cancel the subscription at all, you downgrade it, which changes the payback math again.

What are the real reasons to run a local coding model in 2026?

Privacy, because your code never leaves the machine. Rate limits, because a local model has none and subscription plans do. Availability, because a local model works offline and does not have outages. Control over the model version, because providers deprecate models on their schedule. Cost is on the list only if you are replacing an expensive plan, not a $10 one.

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Hardware August 11, 2026

The Cheapest Hardware That Replaces a $20/mo Coding Subscription (2026)

The r/LocalLLaMA question that never goes away: what is the cheapest hardware that runs a coding assistant good enough to cancel a $10-20/month subscription? We ran the payback math at August 2026 prices and the result is not the one an affiliate site is supposed to publish. A 16GB GPU now costs $589-805 as of August 2026, and against a $10/mo Copilot Pro plan that takes five to seven years to break even, before electricity. If your reason for going local is money, the numbers say stay subscribed.

Bottom Line

We ran the payback math at real August 2026 prices, and it does not say what a hardware affiliate page usually says.

Replacing a $10/mo Copilot Pro plan: do not buy hardware for this reason. Payback is 33-81 months before electricity. The subscription is cheaper than the depreciation.
Replacing a $20/mo Claude Pro plan: no. 16-40 months. Only buy if the non-cost benefits alone justify it.
Replacing a $100/mo Max plan: buy. Payback is 3-8 months and the case is still strong.
Cheapest hardware that genuinely works: RTX 3060 12GB ($329-460 as of August 2026) as the floor, a 16GB card as the pick.
The real reason to go local in 2026: rate limits, privacy, and offline availability. Not the monthly bill.

The math, plainly

Payback period = hardware cost ÷ monthly subscription. Here it is across the plans people actually hold, at prices verified in August 2026.

Hardware	vs Copilot Pro $10/mo	vs Claude Pro $20/mo	vs Copilot Pro+ $39/mo	vs Max $100/mo
RTX 3060 12GB ($329-460)	33-46 months	16-23 months	8-12 months	3-5 months
RTX 5060 Ti 16GB ($589-805)	59-81 months	29-40 months	15-21 months	6-8 months
Used RTX 3090 24GB (~$1,150)	115 months	58 months	29 months	12 months
Mac mini M4 16GB (~$799)	80 months	40 months	20 months	8 months

All hardware prices checked August 2026. They are ranges rather than single figures on purpose — GPU street prices have moved several times this year and a point estimate would be wrong within weeks. The RTX 4060 Ti 16GB is the card this comparison used to recommend; we could not verify a current US price for it in this pass, so it is not in the table. It is certainly well above its $499 MSRP, and we would rather leave it out than publish a guess.

Subscription prices as published in 2026: GitHub Copilot Free / Pro $10 / Pro+ $39 / Max $100 / Business $19 per seat, with Pro including $10 of monthly AI credits. Claude Pro is $20/month with Claude Code at limited usage; Claude Code on the Max plan is $100/month.

Electricity is not in that table and it makes every number worse. A mid-range GPU under sustained agent load adds a few dollars a month; a 24GB card driving an agent all day adds meaningfully more. Our local LLM electricity cost break-even page has community-reported power bills in the $46-93/month range for 24/7 setups — which, on a $10/month subscription comparison, means the local option can cost more per month to run than the thing it replaced.

That is the sentence the genre omits. Against a cheap plan, local AI is not a cheaper way to get the same thing. It is a different thing you buy for different reasons.

Why this got worse in 2026

The payback periods above roughly doubled in a year, and not because subscriptions got cheaper.

Memory chips now account for more than 80% of a GPU’s bill of materials, and the AI data center buildout pushed PC DRAM contract prices up 105-110% in a single quarter. NVIDIA has prepared GeForce RTX price increases of 20-30%, the third such move since January 2026. The RTX 5060 Ti 16GB launched at a $429 MSRP and traded between $589 and $805 in August 2026.

So the hardware side of this comparison inflated while the subscription side held. A calculation that worked in 2025 does not work now. Full detail in should you buy RAM now.

The reasons that survive the math

Cost was never the strongest argument. These are:

Rate limits. Subscription plans meter you and the metering lands mid-task. A local model does not. If you have ever been cut off three files into a refactor, you already know what this is worth — see how to stop hitting Claude Code usage limits for the free mitigations first, before you spend $600 or more.

Privacy. Proprietary code never leaves the machine. For contract work with client NDAs this is not a preference, it is a requirement, and it has no price comparison.

Availability. Local models work offline and do not have provider outages or deprecation schedules. The model you validated against your codebase stays the model you use.

Token economics of agents. Agent harnesses burn tokens at a rate that surprises people — we captured a 40-token prompt becoming a 20,538-token request in the real token cost of an agent. If you run autonomous loops, your effective subscription cost is much higher than the sticker, and the payback table above is too pessimistic for you specifically.

That last point is the important qualifier. The heavier your usage, the better local looks — and the table assumes you are comparing against a plan you are not maxing out.

What to actually buy

The floor: RTX 3060 12GB (~$329-460)

Price check, August 2026: $329-460, not the ~$300 this section used to quote. NVIDIA revived this SKU during the shortage and it now sells at or above its 2021 launch price, which is worth sitting with — the budget anchor of the last five years is no longer a budget card. At the top of that range, Intel’s Arc B580 12GB at around $300-310 is the better buy.

12GB runs 8B-class models at Q4_K_M with usable context. This is genuinely enough to drive a local coding agent for routine work — completions, refactors, test generation, commit messages. It is not enough for hard multi-file reasoning.

The pick: RTX 5060 Ti 16GB

Price check, August 2026: we could not verify a current US street price for the RTX 4060 Ti 16GB in this pass, so treat the old “$450-500” as stale and assume it now sits well above its $499 MSRP. The 16GB card we can price is the RTX 5060 Ti 16GB at $589-805 — it launched at a $429 MSRP and its median has run up to 88% above that. Check both before you buy; the ordering between them changes week to week.

16GB is where local coding stops being a compromise. 14B-class models at Q4 fit with real context, and MoE models with a few active billion parameters run fast. If you are buying once and want the purchase to hold up, buy 16GB — just note that “16GB for under $500” is no longer a thing you can reliably do.

The stretch: used RTX 3090 24GB (~$1,000-1,300)

24GB opens 27-35B models, which is where local coding quality gets genuinely competitive. But at August 2026 used prices this is a $1,150 purchase, which only makes sense against an expensive plan. Read how to buy a used RTX 3090 safely first — the used market has real hazards.

If the non-cost reasons are your reasons, these are the buys:

MSI RTX 3060 12GB — the cheapest card that runs a real local coding agent.
MSI RTX 4060 Ti 16GB — 16GB, the tier where local coding stops feeling like a downgrade.
EVGA RTX 3090 24GB — if you are replacing a $100/mo plan and want 27B-class models.

Amazon affiliate links — we earn a small commission at no cost to you. We would rather you buy the right one, or none.

The outcome most people actually reach

Almost nobody cancels outright. They downgrade and route.

Repetitive, high-volume, privacy-sensitive work goes to the local model. Hard multi-file problems escalate to the frontier model on a cheaper plan. That pattern keeps showing up independently in community threads, and we wrote up the routing rules in hybrid routing: local vs frontier.

It also changes the math one more time, in local’s favour: you are not comparing hardware against the full subscription, you are comparing it against the difference between your current plan and a cheaper one. Dropping Max ($100) to Pro ($20) saves $80/month, which pays off a $475 card in six months while you keep frontier access for the hard problems.

That is the honest recommendation. Not “cancel and buy a GPU” — downgrade and buy a GPU.

Before you spend anything

Try the free options first. If your problem is rate limits rather than cost, stop hitting Claude Code usage limits lists verified open-source tools that stretch an existing plan considerably. Several people who were about to buy a GPU did not need to.