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Opinion page / measured product / rank 11

Zed Reviews and Ratings (2026)

Reader ratings for Zed, aggregated on the same 0 to 100 scale we use for the lab index, with our own commentary underneath. If you are looking for Zed opiniones, reviews or a rating you can check, the measurements behind every claim are on the Zed benchmark page.

Reader index

79.79

3 voters, 28 axis scores. Never blended into the lab index.

Lab index

72.17

Measured on the vibeOps spec

Strict pass rate

71.1%

32 clean and 8 failed executions

Median per prompt

31.4 s

p90 54.5 s

Reader index

One score per reader per axis on a 0 to 100 scale, editable at any time.

Reader index

79.79

Lab index

72.17

3 readers, 28 axis scores, last change 12 Aug 2026. Readers rate Zed 7.6 points above the measurement.

Reader mean against the measured lab subscore for each axis
AxisWeightLabReadersVotesReader mean
Agent performance18%77.086.73
Reliability18%71.181.33
Scalability13%70.078.02
SEO and GEO12%55.058.02
API and MCP9%66.077.73
Integrations8%64.069.73
Design output7%64.073.73
Speed7%100.0100.03
Value5%86.094.73
Code ownership3%99.0100.03

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 Zed

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 Zed

Written by readers with an account. Sorted by upvotes, then by date.

  • Fastest loop I have measured, and I timed it properly

    Lydia Mwangi | 09 Aug 2026

    I sat with a stopwatch across nine prompts because I did not believe the published median. It held up: the wait between asking and having a reviewable diff was consistently under a minute for the small prompts. What the number does not tell you is why. It is not that the model is faster, it is that nothing else in the loop is slow. The diff renders instantly, the editor does not stall while the agent works, and accepting a change does not trigger a reindex you have to wait through. Correctness is mid table, so my honest read is that you get more attempts per hour rather than better attempts.

    • Catarina Ferreira | 10 Aug 2026

      Same conclusion from the free side. Bring your own key and the licence cost is zero, so more attempts per hour is close to more attempts per euro.

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Open rating distribution

Open ratings submitted without an account. Neither the lab index nor the reader index is part of this average.

Reader rating distribution
BandShareRatings
90 to 1000
80 to 890
70 to 790
60 to 690
0 to 590

Lab commentary

Our reading of the numbers, kept separate from the reader ratings.

The fastest median in the index, and the reason is architectural rather than clever prompting: the editor is fast, the diff review is instant and almost no time is lost to interface latency. Correctness sits in the middle of the agent group, so the right read is that it costs the least time per attempt rather than that it is the best at any single attempt.

On the measured axes, Zed is strongest at speed with a subscore of 100.0 and weakest at seo and geo at 55.0. Because seo and geo carries 12 of the 100 index points, that weakness costs it roughly 5.40 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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Rate Zed

One rating per person per product, on the same 0 to 100 scale as the lab index. Ratings without a body are discarded. We publish the name you enter, so use what you are happy to see in public.