Published · 1h agoBuild2 min read
Graft reports 66% against 54% on SWE-bench Verified. At 50 instances a side, that is p 0.22
The Graft README gives the resolve rates and the harness that graded them, but not the instance count. Fill in a plausible one and the 12-point gain fails a standard two-proportion test.
Written for builders.See today for builders

What happened
- Graft's GitHub README states that correctness was measured on SWE-bench Verified and graded by the official harness, with Graft resolving 66% of instances tested against Cold Claude Code's 54%.
- The same README describes efficiency as a 162-run controlled benchmark using the same agent and the same file tools, with only the context differing between variants.
- The README does not state how many SWE-bench Verified instances were run in either the Graft arm or the cold arm; it refers only to "instances tested".
- The harness ran three variants of the same Claude Sonnet 5 agent with the same file tools, including a cold variant that explores from zero and a Graft variant fed a graft ask --source bundle.
- The README frames the claim as an agent reading the graph being cheaper and faster "without getting more answers wrong", and says they measured it rather than asserting it.
Compiled by The EngineerSomething wrong?How this is made
Why it matters
The arithmetic gets unforgiving at small n, and the page never says what n was [3]. Assume fifty instances per arm, the size at which the published rates land at p about 0.22 two-sided [3]. At that size, 66% is 33 tasks resolved and 54% is 27 [5]. The entire headline is six instances.
Pooling the arms gives a 60% resolve rate [2] and a standard error on the difference of just under ten points, so a 12-point gap [1] sits about 1.2 standard errors from zero. To push those same two rates under p<0.05 you would need roughly 128 instances in each arm [4]. That is grading work somebody pays for, and it is not the reader.
None of this is a complaint about the harness. Official grading settles whether a patch resolved an instance [1]. It has nothing to say about how many instances you need before a difference in resolve rates means something.
The odd part is the asymmetry inside one README. The efficiency claim carries its design on its face: 162 runs, same agent, same file tools, only the context differs [2]. The correctness claim, which the page positions as the guardrail that the agent is not getting more answers wrong [5], arrives with no count at all. PlanetScale's Metal page does the same in another domain, reporting an average 70% decrease in p99 and p95 latency from a few customer workloads without saying how many [6]. Denominators are the first thing to fall off a benchmark page.
As published, 66 against 54 supports "not worse". It does not yet support "better".
Claim ledger
Ranked by verification strength, evidence, and original report placement.
- [1]
Graft's GitHub README states that correctness was measured on SWE-bench Verified and graded by the official harness, with Graft resolving 66% of instances tested against Cold Claude Code's 54%.
- [2]
The same README describes efficiency as a 162-run controlled benchmark using the same agent and the same file tools, with only the context differing between variants.
- [3]
The README does not state how many SWE-bench Verified instances were run in either the Graft arm or the cold arm; it refers only to "instances tested".
- [4]
The harness ran three variants of the same Claude Sonnet 5 agent with the same file tools, including a cold variant that explores from zero and a Graft variant fed a graft ask --source bundle.
ReportedView cited source - [5]
The README frames the claim as an agent reading the graph being cheaper and faster "without getting more answers wrong", and says they measured it rather than asserting it.
ReportedView cited source - [6]
PlanetScale's Metal page says real customer workloads saw an average of 70% decrease in p99 and p95 latency, illustrated by graphs covering "a few of our workloads" moved from network-attached storage to Metal, without stating how many workloads.
Sources & coverage · 2 publishers
The reporting this story was synthesized from, earliest first. Every link goes to the original.
Cited in this coverage: NanoNets/Graft README, github.com
- planetscale.com1h agoMetal — PlanetScale
Additional citations
- PlanetScale Metal product page


