What is the cheapest AI assistant for coding?

Why the Sticker Price Lies: The Real Cost Problem

You can buy an AI coding assistant today for $0, $10, or $20 a month — and still end up paying $500 per developer. The sticker price on a pricing page tells you almost nothing about what a tool actually costs your team, because the market has fragmented into three billing models that behave nothing alike.

Flat subscriptions like GitHub Copilot Pro at $10/month look simple, but exhaust your credits and you're buying more. Cursor auto-switches to pay-as-you-go API billing when limits hit, while Claude Code requires opt-in prepaid credits billed at API rates. Then there's the BYOK world — tools like Cline, Aider, Void, and Codex are free to install, but you pay per-token to your model provider, so cost scales entirely with usage.

The gap between sticker price and reality is not theoretical. Gartner data cited in recent pricing analysis shows nearly 25% of organizations now spend $200–$500 per developer per month on AI coding tokens alone, with roughly 6% exceeding $2,000. Cursor's own documentation admits that daily agent users typically land at $60–$100/month despite the $20 Pro price.

The culprit is agent workflows, not autocomplete. Multi-file agent sessions burn 3–8 credits each against typical free allowances of 25–50 credits per month, which is why heavy users blow through limits in days. One documented case: a six-developer team racked up $3,100/month in overages — more than $500 per developer — on top of their seat costs.

So "cheapest" needs redefining around three questions:

• **What's your usage profile?** Light solo devs often win with free tiers or $10–$20 subscriptions; agent-heavy users frequently pay less with flat plans.
• **What does the billing model do at your volume?** Credit systems and per-token BYOK diverge dramatically at scale.
• **What hidden costs follow?** Security review alone can dwarf subscription fees for teams shipping AI-generated code.

Vendor pricing also shifts constantly — one comparison author warns it changes every few weeks, and free tiers get discontinued without warning, as Sourcegraph Cody Free was in July 2025. At SkillzBench, where we're building independent benchmarking for agent tooling, we treat pricing data the same way we treat skill quality: verify before you trust it. The rest of this article prices the major tools against real-world usage, so you can find the genuine cheapest option for how you actually work.

The Actual Cheapest Options: Free Tiers, BYOK Tools, and $10 Entry Points

Strip away the marketing and the "cheapest" question has three real answers: $0, free-but-capped, and $10. Which one wins depends less on the tool and more on how often you actually use it.

Path one: $0 with bring-your-own-key tools. Open-source options like Cline, Aider, Void, and Codex cost nothing to install and have no paid tier at all — you pay only per-token API costs to whichever model provider you connect, according to the PricePerToken pricing tracker. For privacy-focused developers, pairing Continue.dev with Ollama delivers unlimited completions and chat on local hardware, though you'll need 16–32GB of RAM to run it comfortably.

Path two: the strongest free tiers. If you want a hosted product at zero cost, the research points to three standouts:

• Codeium — unlimited free autocomplete and chat, plus 25 monthly Cascade agent credits
• Gemini Code Assist — 6,000 completions and 240 chat requests per day, with Gemini CLI adding another 1,000 daily requests
• GitHub Copilot Free — 2,000 completions and 50 chat messages per month, and notably the cheapest way to get an MCP-capable agent, since MCP works even on the Free tier

One caveat: free tiers aren't guaranteed forever. Sourcegraph Cody Free was discontinued in July 2025, and Gemini's individual tier has been transitioning to the Antigravity CLI, per a daily.dev roundup of no-credit-card tools.

Path three: the cheapest serious paid tier. GitHub Copilot Pro at $10/month is the consensus answer, with Sourcegraph Cody's paid tier starting at $9 and Supermaven matching Copilot at $10. Anything above that — Windsurf at $15, Cursor at $20, Claude Code at $20 monthly ($17 annual) — moves you into a different budget class.

But sticker price is where most buyers get burned, because agent workflows, not autocomplete, drive real costs. A single multi-file agent session burns 3–8 credits against typical free allowances of 25–50 per month. Cursor's own documentation admits daily agent users typically land at $60–$100/month despite the $20 Pro price, and Gartner data cited in industry coverage shows nearly 25% of organizations spend $200–$500 per developer per month on AI coding tokens alone. Anthropic's own numbers put average Claude Code spend at $13 per developer per active day — roughly $260 monthly.

The usage-profile rule from the research is simple: light users win with free tiers or a $10 flat plan, heavy daily agent users win with flat or unlimited subscriptions that cap spend, and occasional users often pay least with BYOK per-token billing. As PricePerToken puts it, the break-even depends entirely on your monthly token volume.

Whichever path you choose, verify current pricing before committing — one comparison author warns vendor pricing "changes every few weeks." And if you're wiring up agents with skills and MCP tools, it's worth knowing which of those components are actually safe: published research found roughly 26% of agent skills carry at least one vulnerability, which is why we're building SkillzBench to scan, benchmark, and trust-score the skills you connect — join the waitlist to follow the launch.

Budget for the true cost, not the entry point. The subscription fee is rarely where the money goes.

The Hidden Costs That Break the 'Cheapest' Math

A $10 subscription can quietly become a $200 monthly habit. The sticker price on an AI coding assistant tells only a fraction of the story, because the real spending happens after checkout — in credits, reviews, and rework.

Agent workflows are the biggest budget killer. Autocomplete is cheap, but multi-file agent sessions burn 3–8 credits each against typical free allowances of 25–50 credits per month, according to a free-tier breakdown. Cursor's own documentation admits daily agent users typically land at $60–$100 per month despite the $20 Pro plan, and Gartner data cited by one pricing analysis shows nearly 25% of organizations now spend $200–$500 per developer per month on coding tokens alone.

Then there's the security bill. Endor Labs' total cost analysis found that 62% of AI-generated code is insecure by default, and AI-assisted developers are twice as likely to write vulnerable code. For a 300-developer team, that translates to an estimated $1.8M per year in manual review costs — plus roughly $12M per year in unaddressed risk. Suddenly, the "cheapest" tool is the one that generates the most cleanup.

The productivity math is equally contested:

• Google and GitHub studies report 21–55% faster task completion with AI assistance, per a ROI analysis.
• METR's July 2025 randomized trial found experienced open-source developers were 19% slower when using AI tools.
• PR review time rose 91% in high-adoption teams, and production incident probability per merged PR more than tripled.

So which numbers do you trust? The honest answer is that both can be true: autocomplete-heavy work speeds up, while complex agent-driven changes demand more oversight. The gap between the two is exactly where hidden costs live.

This is why "cheapest" should mean total cost, not sticker price — subscription plus credits plus review time plus risk. That's also the philosophy behind SkillzBench: before trusting any skill or agent setup, verify what it actually does in a sandbox, with security and quality signals measured separately from marketing claims. A tool that looks free but doubles your review burden isn't cheap; it's just billing you in a different currency.

Budget accordingly: set hard spend caps, reserve cheap models for routine tasks, and audit your invoices weekly for the first 60 days. The teams that treat AI assistants like any other infrastructure cost — measured, capped, and reviewed — are the ones that actually come out ahead.

How to Pick and Budget: A Decision Framework

The sticker price tells you almost nothing about what you'll actually pay. Cursor's own documentation says daily agent users typically land at $60–$100 per month despite the $20 Pro plan, and Gartner data indicates nearly 25% of organizations spend $200–$500 per developer per month on AI coding tokens alone — one six-developer team racked up $3,100 in monthly overages on top of seat costs.

Start by matching the pricing model to your usage profile. Light users do best on free tiers or the cheapest paid plans like Copilot Pro at $10/month. Heavy daily agent users usually win with flat or unlimited subscriptions, since a hard spend ceiling beats unpredictable overages. Occasional users often pay less with BYOK per-token billing, because the break-even depends entirely on monthly token volume, as pricing analysis points out.

Then budget for the true cost, not the advertised one. Agent workflows — not autocomplete — are the main cost driver, burning 3–8 credits per multi-file session against typical 25–50 credit free allowances. Practical guardrails:

• Set hard spending caps on every tool and account before the first agent session runs.
• Audit spend weekly for the first 60 days to catch overage patterns early.
• Route routine tasks to cheaper models and reserve premium models for genuinely hard work.
• Factor in security review — 62% of AI-generated code is insecure by default, so remediation costs can dwarf subscription fees.

Adopt the hybrid approach that Forrester's Charlie Dai recommends: use AI-assisted "vibe coding" for prototyping and experimentation, but rely on traditional coding for complex production work. Pair that with prompt and context engineering optimization, and lean on free tiers for experimentation before committing budget. Dion Hinchcliffe of Futurum adds a complementary tactic — usage discipline and matching the right model to the right task.

Finally, verify pricing before you buy, because tiers change every few weeks. Sourcegraph discontinued its Cody Free tier in July 2025, and Gemini Code Assist's individual free tier has since transitioned as well. Whatever you sign up for today may look different next month, so check the vendor's pricing page immediately before purchase.

One more lens worth applying: the tool matters less than implementation. A structured ROI analysis argues the only defensible way to pick an assistant is a controlled A/B test on your specific codebase and team — ROI arrives in 3–6 months only with intentional rollout, not from chasing the lowest sticker price.

At SkillzBench, we apply the same discipline to the broader agent ecosystem — verifying and benchmarking agent skills so teams know what actually works before they spend on it. Join the waitlist to follow the research as it ships.

Cheap Tools, Trusted Skills: Keeping Your Low-Cost Stack Safe

A $10 subscription can quietly become a $500-per-developer problem — and the most expensive line item often isn't the subscription at all. Security research estimates that a 300-developer team faces roughly $1.8M a year in manual review costs and ~$12M in unaddressed risk from AI-generated code. Cheap tools are only cheap if what you load into them is safe.

That risk extends beyond the model to the skills you attach to it. Published research found that roughly 26% of agent skills carry at least one vulnerability, and an unvetted SKILL.md package can quietly erase months of savings in a single incident. The economics compound badly: one analysis found AI-assisted developers are twice as likely to write insecure code, while production data shows incident probability per merged PR more than tripled on high-adoption teams, with PR review time up 91%.

This is why SkillzBench exists. Free tiers and BYOK tools are a legitimate way to keep costs down — but the instruction packages you bolt onto Claude Code, Codex, Cursor, or Gemini CLI deserve the same scrutiny as the tools themselves. SkillzBench is building two pillars to make that practical:

• Verify — pin every skill version to a commit SHA, then run license checks, security scans, and quality judgment before a skill reaches your agents.
• Benchmark — test every skill in a sandbox with the same model, with and without the skill, and publish the resulting Lift score in percentage points.
• A 0–100 trust score built from security, quality, license, maintenance, and community signals — with Lift always shown separately, because money never touches scores.

The point isn't to add cost to a lean stack; it's to protect the savings you fought for. A $0 BYOK setup with one compromised skill is more expensive than a $20 subscription with none. If you're keeping your coding stack cheap, keep it safe too — join the SkillzBench waitlist to get early access to skill verification and benchmarking as they launch. Skills, proven.