Kimi K3 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing

Kimi K3和GPT-5.6 Sol在软件工程能力测试DeepSWE上来了一次正面交锋，结果让人意外：这两个AI不仅各有胜负，而且互补性极强，组合起来用效果远胜单打独斗。核心亮点是——GPT-5.6 Sol在“一次就答对”上更准，但Kimi K3在“多试几次”上更稳，而且成本便宜六成多。通俗点说，DeepSWE就像一场AI编程考试。GPT-5.6 Sol是那种“第一感觉最准”的选手，给一次机会就答对的概率更高；而Kimi K3虽然第一回合略逊一筹，但给它更多尝试机会后，成功率反超，考卷难度越高优势越明显。关键在于，两个模型出错的地方几乎不重样，GPT-5.6 Sol做错的题Kimi K3往往能答对，反过来也一样。于是测试团队尝试“先让Kimi答题，答不上来再交给GPT”，结果113道题里解出108道，比任何一个单独出战都强。这项对比最直观的影响在成本和选择上。Kimi K3每道题的花费比GPT-5.6 Sol便宜近一半，同样的钱能多解决近三倍的任务，而且它开放了权重，意味着更多开发者能拿它做定制。对普通用户来说，这意味着未来AI编程工具会更便宜、更好用，企业也可能根据任务难度自动切换不同AI来省钱提效，最终让AI服务的价格降下来、质量提上去。

SummaryGPT-5.6 Sol edges Kimi K3 on single-shot quality, but Kimi wins on pass@k with k > 1 and costs 64% less per completed task. The two models succeed and fail in different ways, which makes routing between them the strongest play on the benchmark.Kimi K3 vs GPT-5.6 Sol is close on DeepSWE pass@1: Sol leads 72.7% to 68.5%, a 4.2 point gap.Give the models more attempts and Kimi K3 pulls ahead. It wins pass@2 (82.0 vs 81.0) and pass@4 (89.4% vs 85.8%).Kimi K3 is far cheaper: \$4.65 per rollout vs \$8.37, and 2.8x more solved tasks per dollar.GPT-5.6 Sol is the more reliable model: it solves more tasks on all 4/4 tries (61 vs 45).The models diverge (0.46 correlation across which tasks they solve correctly and incorrectly) and fail differently, so a Kimi-first cascade that escalates to Sol covers 108 of 113 tasks and reaches about 85.6%. Available now Run Kimi K3 on Together AI Full 1M context, automatic prefix caching, OpenAI-compatible API, served from US infrastructure. Open the playground DeepSWE · Head to Head Kimi K3 vs GPT-5.6 Sol at a glance Metric Kimi K3 GPT-5.6 Sol DeepSWE pass@1 68.5% 72.7% DeepSWE pass@2 82.0% 81.0% DeepSWE pass@4 89.4% 85.8% Coverage (solved at least once) 89.4% 85.8% Reliability (4/4 pass rate) 76.6% 84.5% Tasks solved four-for-four 45 61 Cost per rollout $4.65 $8.37 Solved tasks per $100 14.7 5.3 Median rollout time 66 min 17 min Open weights Yes No In our Kimi K3 vs GPT-5.6 Sol comparison on DeepSWE, a benchmark that tests a model's software engineering ability across many task types and programming languages, the story is not who sits at the top of the leaderboard. GPT-5.6 Sol took the pass@1 crown two weeks ago with 72.7% under DeepSWE's official scoring, the strongest single shot and the highest reliability ever recorded on the benchmark. Kimi K3, the open-weight newcomer, answers on the other axis: 89.4% pass@4, better than every flagship on the board, Sol included, while costing \$4.65 a rollout to Sol's \$8.37. We analyzed all 904 graded rollouts (113 tasks, four trials each, at max effort on both sides) from the published per-trial records at deepswe.datacurve.ai.The DeepSWE scoreboard: pass@1 and pass@kGiven a single attempt, Sol wins clearly: 72.7% to 68.5% under DeepSWE's official scoring. But the gap closes fast. At two attempts Kimi K3 is already ahead, 82.0 to 81.0. At four attempts, Kimi's 89.4% beats Sol's 85.8% by 3.6 points, the best pass@4 of any flagship-tier config on the board.Cost comparison: Kimi K3 vs GPT-5.6 Sol pricingKimi K3: \$4.65 per rollout. GPT-5.6 Sol: \$8.37.Per solved task, Kimi delivers 14.7 solves per \$100 versus Sol's 5.3, about 2.8x the work per dollar.The tradeoff is speed and steps: a median Sol rollout takes 17 minutes against Kimi's 66 (using the Kimi K3 API from Moonshot as of July 25th), with Sol using roughly 40% fewer steps. End-to-end latency should improve as inference providers optimize Kimi K3, though the extra steps are a model-behavior trait.Kimi K3 vs GPT-5.6 Sol by programming languageThe two are tied on Go (79 each). Sol leads Python (74-68), TypeScript (66-60), and JavaScript (75-65). Kimi K3 takes Rust (65-60).Coverage vs reliability: opposite corners of the planeDecompose pass@1 and pass@4 into coverage (tasks solved at least once across four tries) and reliability (tasks solved on all four), and the two models sit in opposite corners. Sol posts 84.5% reliability with 61 tasks