Datasets:

witcheer
/

rtx-5090-benchmarks

Rig: one RTX 5090 32GB (sm_120) · Qwen-AgentWorld-35B-A3B (UD-Q4_K_M) vs base Qwen3.5-35B-A3B (Q4_K_M) · llama.cpp b9653, --reasoning on, native tool-calling, temp 0 · same bounded 12-bug SWE-bench Verified subset used for the t082 Ornith harness study, official swebench grader Question: The original AgentWorld finding ran think-OFF to match the base's banked protocol and explicitly scoped out think-ON as "the real falsification" — AgentWorld is designed to reason about environment transitions, so if the claimed transfer needs reasoning to surface, forcing thinking on should reveal it. Does it?

The numbers

resolved / 12	think-OFF (banked)	think-ON
Qwen3.5-35B-A3B (base)	7	7
Qwen-AgentWorld-35B-A3B (LWM-warmed)	8	8

Same count both ways for both models. But the count hides the real result — look at the per-bug outcomes.

Finding 1 — AgentWorld is bug-for-bug identical, not just count-identical

Every one of the 12 bugs gets the exact same classification (resolved / wrong patch / gave up empty) whether thinking is on or off. The 8 resolved are the same 8. The 3 give-ups are the same 3. The 1 wrong-patch is the same 1. Twelve-for-twelve, zero movement. Thinking mode is not suppressing some latent capability here — there is nothing to unlock. Mean steps did tick up slightly with reasoning on (34.4 vs the native loop's typical ~33/40) but it changed nothing about which bugs got fixed.

Finding 2 — the base moves by exactly one wash

The base isn't perfectly static: astropy-12907 flips resolved→give-up and matplotlib-23314 flips give-up→resolved when reasoning is turned on (seaborn-3187 also shifts from wrong-patch to give-up, without changing the resolve count). Net zero, and with n=12 this is noise-band movement, not a signal — but it's worth naming precisely rather than waving at "flat."

What this closes

The original report explicitly left the door open: "AgentWorld is designed to reason about environment transitions and recommends thinking mode... a think-ON A/B is the real falsification leg." This is that leg, and it closes clean: turning reasoning on does not change AgentWorld's real-bug performance at all. The −2/30 (or, on this smaller 12-bug slice, the +1/12 edge — see caveats) isn't an artifact of an unfair think-OFF protocol suppressing the LWM warm-up's benefit. The model's behavior on these bugs simply doesn't respond to the think toggle, full stop.

Honest caveats

n=12, not the original 30. This reuses the bounded subset already banked for the t082 Ornith harness-as-variable study, chosen for direct comparability and to fit inside a session's time budget. Treat the 8/12 and 7/12 counts as noisy on their own — the load-bearing result is the per-bug identity for AgentWorld (12/12 unchanged classifications), which is a stronger, count-independent signal than a resolve-rate delta.
This 12-bug subset flatters AgentWorld relative to the full 30 (8-7 here vs 14-16 over on the full anchor) — expected sampling variance on a 12-bug slice of a 30-bug set, not a contradiction. The 30-bug think-OFF number remains the authoritative anchor result; this run's job was only to test the think toggle, not to re-litigate the resolve rate.
Engineering note, in case it saves someone the same debugging: there is no literal --think flag on this llama.cpp build (b9653) — the switch is --reasoning on|off|auto (--reasoning-format controls how <think> gets extracted into message.reasoning_content). Smoke-tested before the real run: reasoning_content separates cleanly from content, tool-calls still parse correctly alongside it, and round-tripping the full assistant message (content + reasoning_content) back into multi-turn history doesn't break the template or need any harness code changes. Zero-code-change wiring, confirmed empirically rather than assumed.

Verdict

Reasoning was the last plausible explanation for why the LWM warm-up's claimed +3.4–12.8% transfer doesn't show up on real bugs. It isn't the explanation — the model performs identically bug-for-bug with thinking on or off. Between the original think-OFF result and this think-ON check, the claim has now been tested on the two axes that mattered (synthetic vs real, thinking off vs on) and shows no transfer on any of them for real coding.

Generation: native loop = lib/agentic/native/{tools_repo,run_swebench,agent_loop,client}.py (40-step, temp 0), server flags --jinja -c 32768 --reasoning on, Q4_K_M / UD-Q4_K_M, b9653. Grading = official swebench harness. Banked reports: results/swebench/{agentworld-35b-a3b-think,qwen3-5-35b-base-think}.report.json (think-ON); results/swebench/{agentworld-35b-a3b,qwen3-5-35b-base}.report.json (think-OFF, filtered to the 12-bug subset for this comparison). Chart (reports/agentworld-think-on-null.png): left = the think-OFF→think-ON slopegraph (AgentWorld flat, base flat); right = the per-bug grid, the base's one swap highlighted. Companion: reports/agentworld-lwm-transfer.md (the original think-OFF finding this closes).