TEARDOWN Nº 2 / WHAT A CURSOR SESSION COSTS
What a Cursor session costs, by model
PUBLISHED 2026-08-13 · BY Llorenç Ballester — Chief Burn Officer
Cursor's own documentation says on-demand usage "continues at the same API rates" once your monthly pool runs out. Take that at face value and it turns Cursor Pro's $20 credit into exactly what it sounds like: a raw API budget. We already price a coding-agent session across every model on our board — so here is what $20 of Cursor buys you, by model, and why the answer swings 123x.
At the same session shape, DeepSeek V4 Flash costs $0.0017 per session and Claude Fable 5 costs $0.2085 — 123x apart. Run this workload's own default volume (880 sessions/month) on Claude Fable 5 and you owe $183 against a $20 pool — 9.2x over. On DeepSeek V4 Flash, the same volume costs $1.49: 7% of the pool.
The $20 pool is a real budget, not a request count
Cursor Pro is $20/month, and per Cursor's own pricing docs (captured 2026-08-13), that plan includes “$20” of “Other Models usage included,” and once it's gone, on-demand usage “continue[s] at the same API rates with pay-as-you-go billing.” That is a specific, checkable claim: Cursor is telling you the pool is priced in the same dollars the model provider charges, with no markup on the Individual plan. (Teams and Enterprise add a $0.25 per-million-token surcharge on third-party models — a different lane, not covered here.)
Which means the number that actually decides how far $20 goes isn't a Cursor number at all. It's the model's own API price — which is exactly what our board tracks daily.
One session, 17 prices
We don't have Cursor's own token telemetry — nobody outside Cursor does. What we have is our own published canonical coding-agent workload: a 15,000-token aggregated input, 1,500-token output, 40% of the input served from cache — the same shape this site already prices at /workloads, unchanged for this article. Run it against every model and this is what one session costs:
| Model | Per session | Sessions / $20 | Monthly at default volume | x the pool |
|---|---|---|---|---|
| DeepSeek V4 Flash | $0.0017 | 11,786 | $1.49 | 0.1x |
| DeepSeek V4 Pro | $0.0052 | 3,815 | $4.61 | 0.2x |
| GPT-5 Mini | $0.0054 | 3,703 | $4.75 | 0.2x |
| Gemini 3.5 Flash Lite | $0.0066 | 3,016 | $5.83 | 0.3x |
| Gemini 3 Flash | $0.0093 | 2,150 | $8.18 | 0.4x |
| Claude Haiku 4.5 | $0.0209 | 959 | $18.35 | 0.9x |
| Gemini 3.6 Flash | $0.0256 | 779 | $22.57 | 1.1x |
| Gemini 3.5 Flash | $0.0279 | 716 | $24.55 | 1.2x |
| Gemini Omni Flash | $0.0360 | 555 | $31.68 | 1.6x |
| Gemini 3.1 Pro | $0.0372 | 537 | $32.74 | 1.6x |
| Claude Sonnet 5 | $0.0417 | 479 | $36.70 | 1.8x |
| GPT-5.4 | $0.0465 | 430 | $40.92 | 2.0x |
| GPT-5.5 | $0.0930 | 215 | $81.84 | 4.1x |
| Claude Opus 5 | $0.1043 | 191 | $91.74 | 4.6x |
| Claude Opus 4.8 | $0.1043 | 191 | $91.74 | 4.6x |
| GPT-5.6 | $0.1118 | 178 | $98.34 | 4.9x |
| Claude Fable 5 | $0.2085 | 95 | $183 | 9.2x |
Prices from the board, last confirmed 2026-08-12. “Monthly at default volume” uses this workload's own published assumption of 880 sessions/month (40/day × 22 workdays) — swap in your own volume at /workloads. Estimates at list prices, not invoices, and not Cursor's own accounting.
11 of 17 models blow past the pool at this volume
Nobody runs exactly 40 agent sessions a day on one model forever — this is a fixed yardstick, not a prediction of your bill. But held constant, it makes the spread concrete: 11 of the 17 models we track would burn through a $20 pool before the month is out at this shape and volume, led by Claude Fable 5 at 9.2x — call it 3 days of the month before on-demand billing takes over. The other end of the board, DeepSeek V4 Flash, uses 7% of the same pool for the same monthly volume — the $20 outlasts the month with room to spare.
Manually pinning the flagship model for every step is not a bug in Cursor's pricing — it's the price of that model, passed through honestly. What it means for you is that “which model is selected” is the single biggest lever on how far a fixed monthly credit goes, well before prompt length or session count start to matter.
The caching wrinkle, again
Our first teardown found that Anthropic models won't cache a prefix under a published minimum — 512 on Claude Fable 5, 512 on Claude Opus 5, 1,024 on Claude Opus 4.8, 1,024 on Claude Sonnet 5, 4,096 on Claude Haiku 4.5. It applies here too, with a sharper edge: caching references “the entire prompt — tools, system, and messages — up to and including the block designated with cache_control,” and a request can carry several such breakpoints, each needing to independently clear the minimum at its own cumulative length. An agent tool that caches tool definitions, system prompt and context as separate breakpoints can have some of them land above the line and others below it — nothing in the response tells you which, unless you read the cache token counts yourself.
On Claude Haiku 4.5, our own workload's 40% cache-hit assumption is a best case. If none of it clears the model's 4,096-token minimum, the same session goes from $0.0209 to $0.0262 — 26% more, silently, for a model that is otherwise the cheapest way to run a real coding agent on Anthropic's board.
What to actually do with this
- Know which lane you're in. Auto mode and manual model selection are priced differently in Cursor; only manual selection draws from the $20 pool at the model's own rate, which is the only lane we can price from public numbers.
- Price your own shape, not ours. Our 15,000-in/1,500-out session is a yardstick, not your codebase. Swap in your real prompt size and session count at /workloads.
- Route deliberately, not by default. If the flagship model is 123x the cheapest one for the same shape of work, picking it for every step is a choice with a price tag — see model routing for when the expensive model is actually worth it.
- Watch the cache counters, not just the bill. On Anthropic models, confirm cached tokens are actually being read — see the cache-minimum teardown for exactly how.
Method and limits
Every session price is computed at build time from the pricing board and the coding-agent workload — nothing here is Cursor's own accounting, and we have no visibility into Cursor's actual per-request token usage. The one number in this article that is not ours — the $20 pool and its at-cost overage policy — is Cursor's own stated policy, cited above and dated, and it is the one figure on this page that our own daily watcher does not track: if Cursor changes it, this article goes stale until we notice and update it by hand. Everything downstream of that one fact — the session prices, the spread, the pool math — is recomputed from the board on every deploy. Full rules at /methodology.
Frequently asked questions
How much does a Cursor Pro plan actually cover?
Cursor Pro is $20/month and includes a $20 monthly pool for third-party model usage. Per Cursor's own docs, on-demand usage past that pool continues at the same API rates, billed monthly — so the pool is, by Cursor's own description, a $20 budget denominated in raw model API cost, not a fixed number of requests.
Why does the same task cost so differently depending on the model in Cursor?
Because Cursor's on-demand billing passes through the underlying model's list price with no markup on individual/Pro plans. A model that charges more per token costs proportionally more per agent step — and API price spreads between models routinely exceed 100x, so the same session shape can cost two orders of magnitude apart depending only on model choice.
Does Auto mode avoid this?
Cursor states that Auto mode — where Cursor picks the model — is included at no extra cost and does not draw from the credit pool. That is a genuinely different pricing lane from manually selecting a specific frontier model, which does draw from the pool at that model's own rate. We do not have verified figures for Auto mode's internal rates, so we don't price it here — only manual model selection, which is directly computable from public API prices.
Does prompt caching help inside an agentic tool like Cursor?
It can, but only above each model's minimum cacheable length, and — on Anthropic's models specifically — that minimum applies per cache breakpoint, not to the prompt as a whole. An agent tool that caches its system prompt, tool definitions and context as separate breakpoints needs each one to individually clear the threshold. See our cache-minimum teardown for the mechanics and the cliff it creates.
- AI Tokenomics: what tokens actually cost
- How much does ChatGPT actually cost per prompt?
- Prompt caching: the 90% discount most teams never claim
- Why your AI agent costs 10–40x more than a chat
- Why output tokens cost more than input
- Cut AI costs with model routing
- The cache minimum: why your prompt cache silently does nothing
- The Sonnet 5 price cliff, priced before it happens
- How to read your AI usage export
- → The Burnmeter: measure your own token waste