Opinion page / measured product / rank 20
Aider Reviews and Ratings (2026)
Reader ratings for Aider, aggregated on the same 0 to 100 scale we use for the lab index, with our own commentary underneath. If you are looking for Aider opiniones, reviews or a rating you can check, the measurements behind every claim are on the Aider benchmark page.
Reader index
71.33
3 voters, 28 axis scores. Never blended into the lab index.
Lab index
67.27
Measured on the vibeOps spec
Strict pass rate
68.9%
31 clean and 7 failed executions
Median per prompt
39.4 s
p90 75.7 s
Reader index
One score per reader per axis on a 0 to 100 scale, editable at any time.
Reader index
71.33
Lab index
67.27
3 readers, 28 axis scores, last change 12 Aug 2026. Readers rate Aider 4.1 points above the measurement.
| Axis | Weight | Lab | Readers | Votes | Reader mean |
|---|---|---|---|---|---|
| Agent performance | 18% | 72.0 | 79.7 | 3 | |
| Reliability | 18% | 68.9 | 70.7 | 3 | |
| Scalability | 13% | 64.0 | 65.5 | 2 | |
| SEO and GEO | 12% | 54.0 | 60.5 | 2 | |
| API and MCP | 9% | 62.0 | 67.0 | 3 | |
| Integrations | 8% | 58.0 | 63.0 | 3 | |
| Design output | 7% | 52.0 | 49.7 | 3 | |
| Speed | 7% | 79.7 | 85.0 | 3 | |
| Value | 5% | 94.0 | 100.0 | 3 | |
| Code ownership | 3% | 99.0 | 100.0 | 3 |
The reader index is a weighted mean of reader submitted axis scores using the published index weights, renormalised over the axes readers have scored. It is never blended into the lab index. How this works.
Score Aider
Your scores feed the reader column only. Submitting an axis again edits your existing score rather than adding a second vote.
Reader scores need an account so one person cannot vote twice. Create a reader account or sign in.
Reader scores are published in a separate reader index column. They never move the measured lab index.
Reader lab notes on Aider
Written by readers with an account. Sorted by upvotes, then by date.
Cheapest completed run I have recorded, by a lot
Catarina Ferreira | 13 Aug 2026
I tracked token spend across the nine prompts for four different agents. This one came in at roughly a third of the nearest commercial option and finished the spec, which is the part people leave out when they say the cheap option does not work. The discipline is what makes it cheap: it only reads the files you add, so you are not paying to send a repository through the model on every turn. The cost of that discipline is real too. Anything that needs a change across many files at once is slower and needs more of my attention, and prompt seven took me three attempts to steer.
Rafael Villanueva | 14 Aug 2026
On fixed price client work this is the whole argument. If the margin is the difference between the quote and what I spend, a third of the token bill is the difference between a good month and a bad one.
Lydia Mwangi | 14 Aug 2026
Would be interested in your numbers per prompt if you kept them. The published medians tell you time and not spend, and those two do not rank the same way at all.
Write a lab note
What you built, what broke, what you measured. Short opinions belong in the open rating form further down.
Open rating distribution
Open ratings submitted without an account. Neither the lab index nor the reader index is part of this average.
| Band | Share | Ratings |
|---|---|---|
| 90 to 100 | 0 | |
| 80 to 89 | 0 | |
| 70 to 79 | 0 | |
| 60 to 69 | 0 | |
| 0 to 59 | 0 |
Lab commentary
Our reading of the numbers, kept separate from the reader ratings.
The second fastest median in the whole index and by some distance the cheapest per completed prompt. It works on a small explicit set of files and commits as it goes, which is excellent discipline and also why it scores lower on the prompts that need a change across many files at once. Nothing about it is hosted, so there is no platform risk at all.
On the measured axes, Aider is strongest at code ownership with a subscore of 99.0 and weakest at design output at 52.0. Because design output carries 7 of the 100 index points, that weakness costs it roughly 3.36 points against a perfect result on that axis alone.
Reader ratings and lab measurements answer different questions. A reader rating carries the thing a harness cannot capture: whether the product was pleasant to work with over weeks, how support behaved, whether the bill matched the plan. The lab index carries the thing an opinion cannot: 45 timed executions of the same specification with the failures counted. Read them side by side and treat a large gap between the two as the interesting signal.
0 open ratings
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