Claude Sonnet 4.5 vs Kimi K3
Compare Claude Sonnet 4.5 and Kimi K3 side-by-side. See how these vision models stack up in Object Detection, Classification, Image Captioning, OCR, and Open Prompt.
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Claude Sonnet 4.5 vs Kimi K3 Comparison Table
Evals updated July 10, 2026Pricing updated July 17, 2026
| Property | Claude Sonnet 4.5 | Kimi K3 |
|---|---|---|
| Organization | Anthropic | Moonshot AI |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Sep 2025 | Jul 2026 |
| Context Window | 200K | 1.0M |
| Parameters | 2.8T | |
| License | Proprietary | Modified MIT |
| Pricing per 1M tokens | ||
| Input $/1M | $3.00 | |
| Output $/1M | $15.00 | |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Document Question Answering | ||
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Foundation Vision | ||
Claude Sonnet 4.5 vs Kimi K3: Overview
Claude Sonnet 4.5, released by Anthropic in September 2025, is the company’s most advanced Sonnet-series model, built for high-performance reasoning, coding, and long-horizon agentic workflows. It is a multimodal system that accepts both text and images, with a 200,000-token context window designed for handling large documents and extended interactions. Anthropic highlights its improvements in reliability, reduced sycophancy, and alignment, making it suitable for sustained enterprise use.
The model delivers strong results in coding and autonomous workflows, achieving 61.4% on the OSWorld benchmark and leading performance on SWE-bench Verified. It introduces infrastructure features such as a memory tool (beta), checkpointing for Claude Code, parallel tool use, and tighter integration with VS Code. Compared to Opus, which targets broader reasoning, Sonnet 4.5 is optimized for structured, long-duration tasks. Positioned against leading offerings from OpenAI and Google, it is aimed at enterprise automation, software engineering, and research-intensive applications.
Kimi K3 is a sparse Mixture-of-Experts large language model developed by Moonshot AI, with 2.8 trillion total parameters and a 1-million-token context window. The model activates 16 out of 896 experts per token using the Stable LatentMoE framework, and is built on two architectural innovations: Kimi Delta Attention (KDA), a hybrid linear attention mechanism that enables up to 6.3x faster decoding in long-context settings, and Attention Residuals (AttnRes), which selectively retrieves representations across model depth and delivers roughly 25% higher training efficiency. Together with refined training and data recipes, these structural advances yield approximately 2.5x better overall scaling efficiency compared to its predecessor Kimi K2. The model applies quantization-aware training from the supervised fine-tuning stage onward, using MXFP4 weights with MXFP8 activations for hardware compatibility. Thinking mode is always enabled at launch, with reasoning effort configurable via the reasoning_effort field.
Kimi K3 supports native visual understanding alongside text, accepting image inputs for tasks that combine software engineering and visual reasoning. It targets long-horizon coding, knowledge work, and agentic workflows, and ships in two variants: K3 Max for general chat and agent tasks, and K3 Swarm Max for large-scale parallel processing across many coordinated sub-agents. The model is compatible with the OpenAI SDK via an OpenAI-compatible API. Full model weights are scheduled for release by July 27, 2026 under a Modified MIT license, following the open-weight pattern established by the Kimi K2 model family. A technical report with full architecture, training, and evaluation details is expected to accompany the weights release.
Frequently Asked Questions
Claude Sonnet 4.5 is released under Proprietary, while Kimi K3 uses Modified MIT. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.