Claude Opus 4.7 vs Kimi K3
Anthropic Claude Opus 4.7 | Moonshot AI Kimi K3 | |
|---|---|---|
| Overview | ||
| Company | Anthropic | Moonshot AI |
| Release date | Apr 16 2026 | Jul 16 2026 |
| Access | Proprietary | Open Weight |
| Specifications | ||
Parameters | — | 2.8T |
Context window | 1M | 1M |
| Benchmarks | ||
Nonsense detection BullshitBench v2Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 83% | — |
Agentic coding SWE-Bench ProCan the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | 64.3% | — |
Coding SWE-Bench VerifiedReal coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 87.6% | — |
Multilingual coding SWE-Bench MultilingualLike SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. | 80.5% | — |
Agentic coding CursorBench v3.1Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | 64.8% | — |
Agentic coding DeepSWE 1.0Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. Higher is better. | — | 67.5% |
Next.js coding Next.js EvalsVercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 75% | — |
Agentic terminal coding Terminal-Bench 2.1Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | 66.1% | 88.3%Best |
Agentic terminal coding Terminal-Bench 2.0Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | 69.4% | — |
Multi-step tool use MCP AtlasCan the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better. | 79.1% | 84.2%Best |
Professional tool use JobBenchTests the AI on professional workplace tasks that require using real work tools — the kind of multi-step jobs an office worker handles. Higher is better. | — | 52.9% |
Personal tool use Toolathlon-VerifiedTests how well the AI uses everyday personal tools and apps to get things done — a human-checked version of Toolathlon. Higher is better. | — | 73.2% |
Web browsing BrowseCompCan the AI browse the web and track down hard-to-find answers? Higher is better. | 79.3% | 91.2%Best |
Cybersecurity CyberGymTests the AI on cybersecurity challenges — finding and exploiting software weaknesses inside a safe sandbox. Higher is better. | 73.1% | — |
Multidisciplinary reasoning Humanity's Last Exam · no toolsHumanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | 46.9%Best | 43.5% |
Multidisciplinary reasoning Humanity's Last Exam · with toolsHumanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 54.7% | 56%Best |
Abstract reasoning ARC-AGI-2Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | 75.8% | — |
Advanced math FrontierMath · Tier 1–3Very hard, research-level math problems. Tiers 1–3 are the (still extremely difficult) lower tiers. Higher is better. | 43.8% | — |
Advanced math FrontierMath · Tier 4Very hard, research-level math problems. Tier 4 is the hardest — close to what professional research mathematicians tackle. Higher is better. | 22.9% | — |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 94.2%Best | 93.5% |
Agentic computer use OSWorld-VerifiedCan the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 78% | — |
Agentic financial analysis Finance Agent v2Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better. | 51.5% | — |
Knowledge work GDPval-AAMeasures how well the AI does economically valuable knowledge work, judged against human experts. Shown as a rating (like a chess Elo) — higher is better. | 1753 | — |
Knowledge work GDPval-AA v2economically valuable knowledge work (v2, re-based Elo) | — | 1668 |
Knowledge work GDPval (win/tie rate)How often the AI's work matches or beats a human expert's on real knowledge-work tasks. Higher is better. | 80.3% | — |
Chart reasoning CharXiv ReasoningCan the AI read and reason about complex charts and figures, not just text? Higher is better. | 82.1% | 84.8%Best |
Multimodal reasoning MMMU-ProA tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | 75.2% | 81.6%Best |
Spatial reasoning Blueprint-Bench 2Can the AI reason about space and layout — for example, understanding a floor plan or blueprint? Higher is better. | 24.5% | — |
Long context MRCR v2 (8-needle) · 128k averageTests whether the AI can find specific details buried inside a very long document (around 128k tokens — roughly a long book). Higher is better. | 59.3% | — |
Community preference Arena Elo (Text)Real people chat with two anonymous AIs side by side and vote for the answer they prefer. Votes become a chess-style Elo rating on arena.ai — it measures which AI people actually like, not test scores. Higher is better. | 1503 | — |
Community preference (code) Arena Elo (Code)Like the text arena, but people vote on which AI writes better code. The votes become a chess-style Elo rating on arena.ai. Higher is better. | 1557 | — |
| Timeline | ||
| Release gap | Claude Opus 4.7 shipped 91 days before Kimi K3 | |
Which is better: Claude Opus 4.7 or Kimi K3?
Kimi K3 leads Claude Opus 4.7 on 6 of the 8 benchmarks they both report. Claude Opus 4.7 shipped 91 days before Kimi K3, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Opus 4.7) vs 1M (Kimi K3). Claude Opus 4.7 is proprietary, while Kimi K3 is open weight.
On Terminal-Bench 2.1, Kimi K3 leads at 88.3% vs Claude Opus 4.7 at 66.1%. On MCP Atlas, Kimi K3 leads at 84.2% vs Claude Opus 4.7 at 79.1%. On BrowseComp, Kimi K3 leads at 91.2% vs Claude Opus 4.7 at 79.3%. On Humanity's Last Exam · no tools, Claude Opus 4.7 leads at 46.9% vs Kimi K3 at 43.5%. On Humanity's Last Exam · with tools, Kimi K3 leads at 56% vs Claude Opus 4.7 at 54.7%. On GPQA Diamond, Claude Opus 4.7 leads at 94.2% vs Kimi K3 at 93.5%. On CharXiv Reasoning, Kimi K3 leads at 84.8% vs Claude Opus 4.7 at 82.1%. On MMMU-Pro, Kimi K3 leads at 81.6% vs Claude Opus 4.7 at 75.2%.
Frequently asked questions
Claude Opus 4.7 was released by Anthropic on Apr 16 2026.
Kimi K3 was released by Moonshot AI on Jul 16 2026.
Kimi K3 leads on Terminal-Bench 2.1 — Claude Opus 4.7 66.1% vs Kimi K3 88.3%.
Claude Opus 4.7 leads on Humanity's Last Exam · no tools — Claude Opus 4.7 46.9% vs Kimi K3 43.5%.
Claude Opus 4.7 has a 1M context window; Kimi K3 has 1M.
Claude Opus 4.7 is a proprietary model released by Anthropic. Kimi K3 is an open weight model released by Moonshot AI.
Other comparisons
Claude Opus 4.7 vs GPT-5.6 SolKimi K3 vs GPT-5.6 SolClaude Opus 4.7 vs Gemini 3.5 FlashKimi K3 vs Gemini 3.5 FlashClaude Opus 4.7 vs Muse Spark 1.1Kimi K3 vs Muse Spark 1.1Claude Opus 4.7 vs Grok 4.5Kimi K3 vs Grok 4.5Claude Opus 4.7 vs DeepSeek-V4-ProKimi K3 vs DeepSeek-V4-ProClaude Opus 4.7 vs Mistral Medium 3.5Kimi K3 vs Mistral Medium 3.5