--- title: Kimi K3 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing description: A head-to-head evaluation of Kimi K3 and GPT-5.6 Sol on the DeepSWE software engineering benchmark across 904 rollouts. GPT-5.6 Sol leads on pass@1 (72.7% vs... canonical: https://daily.dev/posts/kimi-k3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing-hnrwmvzdv twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Kimi K3 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing | daily.dev og:description: A head-to-head evaluation of Kimi K3 and GPT-5.6 Sol on the DeepSWE software engineering benchmark across 904 rollouts. GPT-5.6 Sol leads on pass@1 (72.7% vs... og:url: https://daily.dev/posts/kimi-k3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing-hnrwmvzdv og:image: https://api.daily.dev/og/posts/hNrWmVZdv.png og:image:alt: Kimi K3 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Kimi K3 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing **[Together AI](https://daily.dev/sources/togetherai)** · 6 min read · 1 upvotes · 0 comments ## Summary A head-to-head evaluation of Kimi K3 and GPT-5.6 Sol on the DeepSWE software engineering benchmark across 904 rollouts. GPT-5.6 Sol leads on pass@1 (72.7% vs 68.5%) and reliability, but Kimi K3 wins pass@4 (89.4% vs 85.8%) at 2.8x more solved tasks per dollar. The models fail in distinct ways — Sol breaks existing tests more often, Kimi K3 produces near-misses — and have only 0.46 correlation on which tasks they solve. A Kimi-first cascade that escalates to Sol when tests fail reaches ~85.6%, beating either model alone. Together they cover 108 of 113 tasks (95.6%). The post also promotes running Kimi K3 on Together AI's inference platform. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How does Kimi K3 compare to GPT-5.6 Sol on the DeepSWE coding benchmark? GPT-5.6 Sol wins single-attempt quality with a pass@1 of 72.7% versus Kimi K3's 68.5%, and it solves more tasks reliably on all four tries (61 vs 45). Kimi K3 overtakes Sol as attempts increase, reaching 89.4% pass@4 versus Sol's 85.8%, while costing 64% less per completed task and delivering 2.8x more solves per dollar spent. _daily.dev surfaces benchmark comparisons like this for teams weighing model cost against coding reliability._ ### Does routing between Kimi K3 and GPT-5.6 Sol improve coding accuracy over using either model alone? Yes, running Kimi K3 first and escalating to GPT-5.6 Sol whenever a test suite rejects the result reaches about 85.6% accuracy, beating both individual models and even a perfect one-shot router at 83.4%. The two models diverge with only 0.46 correlation on which tasks they solve, together covering 108 of 113 DeepSWE tasks, with Kimi clearing roughly 70% of the queue before Sol is invoked. _engineers building verifier-based agent cascades can track routing strategies like this through daily.dev._ ### What are the typical failure modes of Kimi K3 versus GPT-5.6 Sol on coding tasks? GPT-5.6 Sol breaks the repository's existing baseline tests in 20% of its failures, a pattern consistent with other GPT models. Kimi K3 fails its baseline tests only 11% of the time but has near misses in 65% of failures, where over 80% of new tests pass but a few still fail, meaning it gets close without fully succeeding. _daily.dev helps developers stay on top of model failure patterns before picking a coding agent backend._ ## Similar posts on daily.dev - [GLM-5.3 vs. GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing](https://daily.dev/posts/glm-5-3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing-klsdguyhy) · Together AI · 3 upvotes · 0 comments --- Tags: [#ai](https://daily.dev/tags/ai), [#ai-coding](https://daily.dev/tags/ai-coding), [#ai-gateway](https://daily.dev/tags/ai-gateway), [#kimi](https://daily.dev/tags/kimi) [View this post on daily.dev](https://daily.dev/posts/kimi-k3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing-hnrwmvzdv) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Kimi K3 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing","url":"https://daily.dev/posts/kimi-k3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing-hnrwmvzdv","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/kimi-k3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing-hnrwmvzdv"},"datePublished":"2026-07-27T05:03:33.408Z","dateModified":"2026-10-15T02:22:10.372Z","description":"A head-to-head evaluation of Kimi K3 and GPT-5.6 Sol on the DeepSWE software engineering benchmark across 904 rollouts. 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Kimi K3 overtakes Sol as attempts increase, reaching 89.4% pass@4 versus Sol's 85.8%, while costing 64% less per completed task and delivering 2.8x more solves per dollar spent. daily.dev surfaces benchmark comparisons like this for teams weighing model cost against coding reliability."}},{"@type":"Question","name":"Does routing between Kimi K3 and GPT-5.6 Sol improve coding accuracy over using either model alone?","acceptedAnswer":{"@type":"Answer","text":"Yes, running Kimi K3 first and escalating to GPT-5.6 Sol whenever a test suite rejects the result reaches about 85.6% accuracy, beating both individual models and even a perfect one-shot router at 83.4%. The two models diverge with only 0.46 correlation on which tasks they solve, together covering 108 of 113 DeepSWE tasks, with Kimi clearing roughly 70% of the queue before Sol is invoked. engineers building verifier-based agent cascades can track routing strategies like this through daily.dev."}},{"@type":"Question","name":"What are the typical failure modes of Kimi K3 versus GPT-5.6 Sol on coding tasks?","acceptedAnswer":{"@type":"Answer","text":"GPT-5.6 Sol breaks the repository's existing baseline tests in 20% of its failures, a pattern consistent with other GPT models. Kimi K3 fails its baseline tests only 11% of the time but has near misses in 65% of failures, where over 80% of new tests pass but a few still fail, meaning it gets close without fully succeeding. daily.dev helps developers stay on top of model failure patterns before picking a coding agent backend."}}]} ```