# Together AI adds Kimi.ai's K3 model, says it beats Claude Fable 5 on coding benchmark for about a third of the cost > Source: > Published: 2026-07-24 19:31:53+00:00 Together AI announced that Kimi.ai’s K3 model will be hosted on its platform starting Monday, July 27th, 2026. In a post on X, the company highlighted a benchmark that pitted K3 against Anthropic’s Claude Fable 5 using 452 DeepSWE rollouts. The results, detailed in a blog‑post linked in the tweet, claim that K3 achieves "near‑flagship" coding performance at about 35% of the price of Claude Fable 5, while also pulling ahead on higher pass@k metrics. "We ran 452 DeepSWE rollouts against Claude Fable 5: near‑flagship coding at ~35% of the price, and K3 pulls ahead at higher pass@k's," the tweet read. The DeepSWE suite, an open‑source benchmark that evaluates code generation across a range of software‑engineering tasks, is increasingly used by AI labs to compare model efficiency and quality. Pass@k, the metric referenced in the post, measures the probability that at least one of the top‑k generated solutions passes all test cases – a standard introduced by OpenAI for code‑generation evaluation. A higher pass@k indicates a model’s ability to produce correct code within fewer attempts. Kimi.ai, the creator of the K3 model, has positioned itself as a cost‑focused alternative to larger, more expensive models. By integrating K3 into Together AI’s offering, the company is extending its reach to developers who need high‑quality code assistance without the premium price tag associated with flagship models like Claude Fable 5. Claude Fable 5, the latest iteration of Anthropic’s Claude series, is marketed as a flagship coding assistant, offering strong performance across a variety of programming languages. The claim that K3 can match or exceed Claude’s performance at a fraction of the cost could shift how small and mid‑size teams evaluate model procurement decisions, especially when budget constraints dominate. The blog post linked in the tweet ([Full deep‑dive]([https://www.together.ai/blog/kimi-k3-vs-claude-fable-5-on-deepswe-cost-and-coding](https://www.together.ai/blog/kimi-k3-vs-claude-fable-5-on-deepswe-cost-and-coding))) provides a deeper look at the experimental setup. According to the post, both models were run on identical hardware configurations, and cost calculations were based on per‑token pricing disclosed by the providers. The analysis reports a 65% reduction in total expense for K3 while maintaining comparable pass@1 scores and outperforming Claude at pass@10 and pass@50 levels. Together AI’s platform, which aggregates multiple generative AI models under a single API, aims to give developers flexibility in selecting the best model for a given task. Adding K3 expands its catalog of cost‑effective options and positions the platform as a marketplace where price‑performance trade‑offs are transparent. While the data presented is promising, it is limited to a single benchmark suite and a specific pricing snapshot. The AI‑coding market remains volatile, with providers frequently adjusting token rates and releasing new model versions. Analysts will likely watch how K3’s performance holds up across other benchmarks such as HumanEval and MBPP, and whether the cost advantage persists as usage scales. The announcement arrives amid a broader industry trend of specialized, niche models targeting specific use‑cases at lower cost. Companies like Cohere, Mistral, and Grok have recently launched models that prioritize efficiency over raw size, responding to developer demand for affordable, production‑ready AI. For developers evaluating coding assistants, the combined claim of near‑flagship quality and substantial cost savings offers a concrete data point to inform model selection. If the DeepSWE results translate to real‑world development workflows, K3 could become a go‑to option for teams that need reliable code generation without the expense of flagship models. Together AI will make K3 available to its existing customer base on Monday, with pricing details to be announced on its platform’s pricing page. The move underscores a growing emphasis on cost‑effective AI deployment, a theme that is reshaping investment and product strategies across the generative AI landscape.