I was running into a lot of posts that praised both the Fixed template and the Sharp template in comparison to the stock one, so I put them to the test.

It's not as extensive as it should be for a paper-grade analysis, but it gives out the point of each template.

Test setup

I used SWE-bench Verified with mini-SWE-agent 2.4.6, slice 0:100 (the identical 100 tasks for all runs)

Hardware

• CPU: Ryzen 9 9900X
• RAM: 128 GB DDR5-5600
• GPU: RTX PRO 6000 WS

Runtime

I containerized jpezzulli/sglang-rtxpro6000 and ran Flash Next with RadixArk/Qwen3.8-Flash-Next-NVFP4 on CUDA 13.3.

• Full 262K context
• BF16 KV
• 51.2 GB FP8 n-gram embedding table pinned in RAM
• 32 GB HiCache pinned in RAM

I ran all templates at both medium and xhigh reasoning efforts.

Results

|Metric|Stock (medium)|Stock (xhigh)|Stock Δ|Fixed (medium)|Fixed (xhigh)|Fixed Δ|Sharp (medium)|Sharp (xhigh)|Sharp Δ|
|:-|:-|:-|:-|:-|:-|:-|:-|:-|:-|
|Resolved|91|99|\+8|87|98|\+11|94|94|\+0|
|Resolution rate|91%|99%|\+8 pts|87%|98%|\+11 pts|94%|94%|\+0 pts|
|Median output tokens|5,691|13,855|\+143.5%|6,956|14,819|\+113.0%|8,596|12,008|\+39.7%|
|Median reasoning tokens|3,050|8,759|\+187.2%|3,809|9,063|\+137.9%|5,437|7,967|\+46.5%|
|Median wall time|38s|1m 46s|\+180.4%|43s|1m 47s|\+152.3%|1m|1m 32s|\+53.4%|
|Total wall time|1h 47m 1s|4h 31m 22s|\+153.6%|1h 59m 53s|4h 4m 52s|\+104.3%|2h 29m 18s|3h 11m 36s|\+28.3%|

https://preview.redd.it/02geu81o8qnh1.png?width=1152&format=png&auto=…

https://preview.redd.it/v2mt6mgo8qnh1.png?width=1152&format=png&auto=…

https://preview.redd.it/ph1z36zo8qnh1.png?width=1152&format=png&auto=…

Takeaways

https://preview.redd.it/6ydu12mp8qnh1.png?width=1152&format=png&auto=…

• Raising reasoning effort to xhigh closes almost all of stock's and fixed's gap to Sharp. At medium, Sharp led resolution by +3 tasks over stock and +7 over fixed; at xhigh, stock and fixed instead lead Sharp by +5 and +4 tasks, respectively.
• Sharp barely moves on resolution (94 → 94) despite a real token/time cost increase, median reasoning tokens rise +46.5% and median wall time +53.4%. This suggests it was already extracting most of the benefit it could get from extra reasoning budget at medium, while stock and fixed still had headroom.
• Sharp remains the most token-efficient per resolved task at xhigh (14,541 output tokens/resolved vs. \~17,000 for stock/fixed), consistent with its medium-era efficiency edge, but it's no longer the highest-resolving template once reasoning effort is high.
• Absolute cost scales heavily with reasoning effort: total wall time roughly 2.3–2.5× for stock/fixed and +28% for Sharp; total reasoning tokens roughly doubled for stock/fixed and increased +35% for Sharp.

Conclusion

• Sharp should be used at medium and it keeps a reasonable accuracy at very good speed. I don't see the point in using it at xhigh. By sacrificing a small accuracy you complete the tasks in half the time.
• Stock is the slowest but the most precise.
• Fixed is the middle ground between Stock and Sharp both in accuracy and speed
• The next benchmark will be on a much extensive SWE-bench Multilingual + Terminal Bench.

Disclaimer: I wrote the post myself then used AI to format it properly for readability