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Qodo CLI agent scores 71.2% on SWE-bench Verified

139 points| bobismyuncle | 6 months ago |qodo.ai

54 comments

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gronky_|6 months ago

I’ve been running a bunch of coding agents on benchmarks recently as part of consulting, and this is actually much more impressive than it seems at first glance.

71.2% puts it at 5th, which is 4 points below the leader (four points is a lot) and just over 1% lower than Anthropic’s own submission for Claude Sonnet 4 - the same model these guys are running.

But the top rated submissions aren’t running production products. They generally have extensive scaffolding or harnesses that were built *specifically for SWE bench*, which kind of defeats the whole purpose of the benchmark.

Take for example Refact which is at #2 with 74.4%, they built a 2k lines of code framework around their agent specifically for SWE bench (https://github.com/smallcloudai/refact-bench/). It’s pretty elaborate, orchestrating multiple agents, with a debug agent that kicks in if the main agent fails. The debug agent analyzes the failure and gives insights to the main agent which tries again, so it’s effectively multiple attempts per problem.

If the results can be reproduced “out-of-the-box” with their coding agent like they claim, it puts it up there as one of the top 2-3 CLI agents available right now.

energy123|6 months ago

What are the typical context lengths in SWE-bench problems? Does it partly measure performance in the 64-128k context range?

terminalshort|6 months ago

Is there something in this multi-agent approach that makes the setup more specific to just the test at hand and less general to real engineering tasks? If not, then this multi-agent system will just become what you get out of the box in a future product. Multiple attempts per problem (as long as there's no human intervention or selection between them) is a perfectly fine approach for agents because that's not an issue from the perspective of an engineer using the product. A single agent is already a multi-step usage of LLMs and it sounds like this is just another meta level of that.

eddd-ddde|6 months ago

I think multiple attempts are completely understandable and even expected? How is that defeating the purpose of the benchmark?

szundi|6 months ago

According to your experience with this model, is it just trained for the benchmark or these points are actually representing the performance?

Roritharr|6 months ago

Finally someone mentions Refact, I was in contact with the team, rooting for them really.

ai-christianson|6 months ago

One thing with SWE bench is making sure there's zero leakage of information into the LLM context.

I.e. the agent cannot even know which tests are failing.

It has to both fix the issue based just on the issue text and fix it in the specific way the unit test, which it cannot see, expects.

For this reason I find the benchmark a little disconnected from the reality of software engineering.

khalic|6 months ago

We need some international body to start running these tests… I just can’t trust these numbers any longer. We need a platform for this, something at least we can get some peer reviews

redman25|6 months ago

That sounds like an interesting idea to me. It would at least resolve the problem of companies gaming the metric.

Another approach might be the LiveBench approach where new tests are released on a regular basis.

jcorco|6 months ago

I’m working on this at STAC Research and looking to connect with others interested in helping. Key challenges are ensuring impartiality (and keeping it that way), making benchmarks ungameable, and guaranteeing reproducibility. We’ve done similar work in finance and are now applying the same principles to AI.

mupuff1234|6 months ago

I'm curious how do these LLM wrapper companies think they'll survive long term - especially coding related wrappers.

I could understand focusing on a niche business use case, but coding is a main focus of the foundation models themselves.

M4R5H4LL|6 months ago

Labeling them as “wrappers” and “niche business” indicates a strong cognitive bias already. Value can be created on both sides of the equation.

orangebread|6 months ago

I've been using Warp for the past few weeks and it's been incredibly impressive over other agentic coding services/platforms. Curious how Qodo stacks up.

lightbendover|6 months ago

When I tried warp I was convinced that was where the industry was going (agents as terminal replacement), but it felt a bit too heavy to me so I haven’t been using it lately. Still think all things will converge on terminal and browser replacement.

itamarcode|6 months ago

Unlike most SWE bench submissions, Qodo Command one uses the product directly.

I think that the next step is getting an official "checked" mark by the SWE bench team

raylad|6 months ago

If it's really better than Claude Code while using Sonnet 4.0, then I'd pay a monthly fee for it, but only if I can use my Claude subscription the same way Claude Code does.

I do not want to pay API charges or be limited to a fixed number of "credits" per month.

esafak|6 months ago

If Qodo is reading: please compare your efficiency too. Run some tasks on various agents using the same models, and report the cost.

lirantal|6 months ago

Slick. This applies to the new Qodo Command CLI, yes?

I updated to the latest version last night. Enjoyed seeing the process permission toggle (rwx). Was a refreshing change to keep the security minded folks less in panic with all the agentic coding adoptions :-)

zuzuen_1|6 months ago

I would be more interested in Qodo's performance on the swe-bench-multilingual benchmark. Swe-bench-verified only includes bugs related to python breakages.

The best submission is swe-bench-multilingual is Claude 3.7 Sonnet which solves ~43% of the issues in the dataset.

zuzuen_1|6 months ago

Does anyone have a benchmark on the effectiveness of using embeddings for mapping bug reports to code files as opposed to extensive grepping as Qodo, Cursor and a number of tools I use do to localize faults?

afro88|6 months ago

If Qodo are reading this: please introduce a plan that isn't for teams or enterprise. A "pro" plan for individuals who want more than 250 credits per month.

OldGreenYodaGPT|6 months ago

Was using their bot for code review for last 2 years but just dropped it for BugBot

OldfieldFund|6 months ago

do we know anything about the size of the model? I can't find the answer.

khalic|6 months ago

it's sonnet behind the scene