How Much Should You Spend on a PC? Real Budgets by Use Case, India 2026

How much should you actually spend on a PC?

Most people overestimate what their use case needs and underestimate what their use case actually costs. Across 1,235 real quotes we have written, the median gaming PC came out at ₹1.91 lakh and the median local-AI machine at ₹2.03 lakh — much closer together than almost anyone expects. What separates them is not price. It is where the money goes.

This is a guide to picking the right machine for what you actually do, using what people in India actually bought from us rather than what a spec sheet suggests.

What people actually spend, by use case

Every figure below is the median grand total, including GST, from quotes we issued to real customers.

Use case	Median quote	Typical range (25th–75th)	Quotes
Gaming	₹1,91,230	₹1,53,939 – ₹2,01,353	506
AI / ML	₹2,03,075	₹1,88,159 – ₹3,88,537	98
Content creation	₹2,00,654	₹1,67,133 – ₹2,18,561	61
Workstation	₹1,64,865	₹57,985 – ₹2,12,761	18

Two things stand out.

Gaming is the tightest band. The middle 50% of gaming quotes sit inside about ₹47,000 of each other. That is because gaming has a well-understood ceiling: past a certain point you are buying frames you cannot see on the monitor you own.

AI is the widest. The 75th percentile for AI/ML is ₹3.89 lakh — nearly double the median. There is no natural ceiling. The model you want to run decides the machine, and model sizes do not care about your budget.

The workstation range looks alarming because the sample is small (18 quotes) and "workstation" covers everything from a CAD seat to a render node. Treat that row as indicative, not a benchmark.

Gaming: the resolution decides the budget, not the games

Competitive and AAA are not different budgets. Resolution is.

1080p competitive — around ₹90,000 to ₹1.2 lakh. Valorant, CS2, Apex at high refresh. You want frames, not fidelity. The CPU matters more than the GPU here, which is the opposite of every other category on this page. Do not buy a big graphics card for competitive shooters; buy a fast processor and put the savings into a 144Hz+ monitor, because the monitor is what you actually experience.

1440p, high refresh, AAA — around ₹1.5 to ₹2 lakh. This is where most of our gaming builds land, and it is the sweet spot in India right now. The most-quoted card across our gaming builds is the RTX 5060 Ti at 40% of all gaming GPU lines, followed by the RX 9060 XT at 29%.

4K — ₹2.5 lakh and up, honestly. 4K is the point where the GPU stops being a component and becomes the budget. If you are stretching to reach 4K, buy 1440p and a better monitor instead. You will enjoy it more.

On memory: gaming splits almost exactly in half between 16GB and 32GB — 49% and 48% of our gaming builds. That is a real fork, not a mistake. 16GB is still enough for games alone. 32GB is for people who keep Chrome, Discord and a game open together, which is most people.

Local AI: the surprising part

Here is the finding that contradicts most advice on the internet.

82% of the AI and ML builds we quote use an RTX 5060 Ti. Not a 4090. Not a 5090. A mid-range card.

The reason is VRAM per rupee. For running models locally, the question is almost never "how fast is this card" and almost always "does the model fit in memory". A 16GB card runs a quantised 13B model comfortably. A faster card with less memory does not run it at all. So people buying for local AI optimise for capacity, and the 5060 Ti 16GB is currently the cheapest sensible way to get 16GB in India.

Memory follows the same logic: AI builds are the only category where 64GB shows up meaningfully, at 17% of RAM lines, against 2% for gaming.

Where the money should go if local AI is your use case: VRAM first, system RAM second, CPU last. This is the exact inverse of a competitive gaming build. If you are training rather than inferencing, or running unquantised models above 30B, you are in the ₹3.5 lakh-plus territory that produced our 75th percentile — and at that point a conversation beats a configurator.

Editing and content creation: it depends what you edit

Content creation quotes median ₹2,00,654, which is close to gaming, but the machines look different.

1080p and 1440p video, photo work, design. Around ₹1.2 to ₹1.8 lakh. This is CPU and RAM territory. Timeline scrubbing, exports and Lightroom care far more about cores and memory than about graphics horsepower.

4K multi-cam, heavy colour work, 3D. ₹2.5 lakh and up. Here the GPU starts to matter again — for effects and rendering rather than for playback — and storage becomes a real line item rather than an afterthought.

One thing our data shows that we would push back on: 60% of content-creation builds we quote go out with 16GB of RAM. For pure gaming that is defensible. For editing it is the first thing that will frustrate you. If you edit for a living and have to choose between 32GB and a better GPU, take the memory.

When we would tell you to spend less

We would rather sell you the right machine than the expensive one.

If you play only competitive titles, you are the person most likely to overspend. A ₹1 lakh machine will run CS2 or Valorant at a frame rate beyond what your monitor and your eyes can use. Spend the difference on a monitor and a chair.

If your use case is "it should feel fast", you do not need a new PC tier. You need an NVMe drive and enough RAM. A ₹15,000 upgrade to an existing machine solves this more often than a ₹1.5 lakh replacement.

If you are buying for AI because it is interesting rather than because you have a specific model to run, start with a 16GB card. You can rent a bigger GPU by the hour for less than the price difference, and you will know within a month whether you need one.

If you are waiting on a specific launch, wait. Buying weeks before a successor arrives has always stung.

Choosing, in one pass

• Competitive gaming: ₹90k–1.2L. CPU over GPU. Put money into the monitor.
• 1440p AAA: ₹1.5–2L. The most common build we ship, and the best value in India today.
• 4K gaming: ₹2.5L+. If it is a stretch, buy 1440p and a better screen.
• Local AI: ₹1.9–2.5L for inference on 16GB. VRAM first, RAM second, CPU last. ₹3.5L+ if you are training.
• Editing: ₹1.2–1.8L for 1080p/1440p, ₹2.5L+ for 4K multi-cam. Take 32GB over a better GPU.
• Not sure: describe what you actually do rather than the parts you think you need.

You can see every recent build we have shipped with its full parts list and the benchmarks we measured before it left the workshop — the most honest way to judge what a budget really buys. If you want a machine specified around your use case rather than a tier, that is what our custom PC build service is for, including the version of the conversation where we tell you to spend less. When you are ready for a number, request a quote and you will have one in 4 to 8 hours.

Figures are median grand totals including GST from 1,235 NVSX customer quotes linked to a stated use case, and component share from the line items on those quotes. Sample sizes are shown per row; the workstation row (n=18) and streaming (n=4, omitted) are too small to be treated as benchmarks. Prices reflect August 2026, during a period of rising memory and GPU costs.