LabsMoonshot AI
Moonshot AI
Track Moonshot AI model scores across public AI benchmarks including ECI, EQ-Bench Creative v3, GPQA Diamond, SWE-bench Verified, and WeirdML. Each result is shown one benchmark at a time, with source links and evaluation dates — no blended score or composite ranking. 4 models tracked, spanning Kimi and Kimi K2.
Models 4
Kimi K2.6
Kimi · kimi-k2.6
2026-04-20
32 results
Kimi K2.5
Kimi · kimi-k2.5
2026-01-27
35 results
Kimi K2 Thinking
Kimi K2 · k2 thinking
2025-11-06
15 results
Kimi K2 Instruct
Kimi · kimi-k2
2025-07-11
19 results
Progress by benchmark
Show progress on
Single benchmark only
This view shows Epoch Capabilities Index (Index) only. Other benchmarks use different metrics and are not directly comparable.
Progress matrix
| Model | SWE-bench Verified % resolved | Terminal-Bench 2.1 task success | DeepSWE % resolved | GPQA Diamond accuracy | LiveCodeBench Pro Codeforces Elo | Humanity's Last Exam accuracy | LiveBench score | SWE-bench Pro % resolved | Berkeley Function Calling Leaderboard accuracy | MMMU-Pro accuracy | LMArena source-defined rating | ARC-AGI-1 accuracy | ARC-AGI-2 accuracy | ARC-AGI-3 accuracy | FrontierMath accuracy | AIME (OTIS Mock) accuracy | SimpleQA Verified accuracy | GBA Eval overall score | WeirdML average accuracy | MCP Atlas pass rate | Remote Labor Index automation rate | Artificial Analysis Intelligence Index Index | Epoch Capabilities Index Index | Aider Polyglot % correct | SWE-rebench Resolved rate (pass@1) | MMLU-Pro accuracy | OSWorld task success rate | GAIA: A Benchmark for General AI Assistants accuracy | BrowseComp accuracy | τ²-bench (Telecom) pass^1 | AIME 2026 accuracy | MathVista accuracy | Video-MME accuracy | GDPval Elo | LiveCodeBench Pass@1 | METR Task-Completion Time Horizons 50% time horizon | SciCode accuracy | MMMU (Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark) accuracy | AA-Omniscience: Knowledge and Hallucination Benchmark AA-Omniscience Index | IFBench accuracy | MultiChallenge accuracy | OpenAI-MRCR v2 (Multi-Round Coreference Resolution) accuracy (mean SequenceMatcher similarity) | LongBench v2 accuracy | Global-MMLU accuracy | Video-MMMU accuracy | WebDev Arena Elo | Search Arena Elo | Arena-Hard-Auto v2.0 % win rate | EQ-Bench Creative Writing v3 Elo | Design Arena Elo | AILuminate AI Safety Benchmark Safety grade | MASK (Model Alignment between Statements and Knowledge) Honesty score | MCP-Universe Overall Success Rate | CharXiv accuracy | OCRBench v2 accuracy | ScreenSpot-Pro accuracy | FACTS Grounding Grounding accuracy | BigCodeBench calibrated Pass@1 | SWE-bench Multilingual % resolved | SWE-bench Multimodal % resolved | SuperGPQA accuracy | EnigmaEval accuracy | ZeroBench accuracy | IMO-Bench accuracy | PutnamBench Problems solved | MathArena HMMT February 2026 accuracy | FrontierMath Tier 4 accuracy | Vectara Hallucination Leaderboard Hallucination Rate | Gray Swan Arena (Agent Red-Teaming / Indirect Prompt Injection) Attack Success Rate (ASR) | PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts Difficulty-Weighted Accuracy (DW-ACC) | Vibe Code Bench Overall accuracy | Online-Mind2Web Task success rate | WebArena Task success rate | GSO: Software Optimization Benchmark for SWE-Agents Opt@1 | MultiNRC accuracy | Terminal-Bench 2.0 task success | SWE-Marathon resolution rate (pass@1) | FrontierCode weighted score (Diamond) | FrontierSWE dominance score | ProgramBench almost-resolved rate | CursorBench score | PostTrainBench weighted average score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Kimi K2 Instruct Kimi | — | — | — | — | — | — | — | 27.67% | 59.06% | — | — | — | — | — | — | — | — | — | 39.4% | 23.9% | — | 26.3 | 141.2 | 60.0% | — | 84.8% | — | — | — | 65.8% | — | — | — | — | 85.3% | — | 42.4% | — | — | — | — | — | 44.3% | — | — | — | — | — | 1738 | 1088 | — | 46.67 | — | — | — | — | — | — | — | — | 57.2% | — | — | 45.8% | — | — | — | — | — | 65.1% | — | — | — | 4.9% | — | — | — | — | — | — | — | — |
| Kimi K2 Thinking Kimi K2 | 71.3% | — | — | 84.5% | — | 23.9% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 145.6 | — | — | 84.6% | — | — | 60.2% | — | — | — | — | 992 | — | — | — | — | — | — | 55.42% | — | — | 73.5% | — | 1329 | — | — | 1695 | — | — | — | 26.41% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 4.8% | — | — | — | — | — | — | 35.7% | — | — | — | — | — | 7.25% |
| Kimi K2.5 Kimi | 73.8% | — | — | 87.6% | — | — | — | — | — | — | — | 65.33% | 11.81% | — | 27.9% | 92.2% | 33.9% | — | 45.6% | — | — | 46.8 | 148.2 | — | 58.5% | — | — | 38.1% | — | — | 95.83% | — | 87.4% | 1285 | — | — | 49.0% | — | — | — | 61.39% | — | — | 84.0% | 86.6% | 1431 | — | — | 1593 | 1292 | — | 70.47 | — | 77.5% | — | — | — | — | 67.3% | — | — | 3.38% | — | — | — | 87.12% | 4.2% | 14.2% | — | — | 17.54% | — | — | — | 35.17% | — | — | 1.0% | 26% | — | 31.9% | 10.26% |
| Kimi K2.6 Kimi | 76.7% | — | 23.89% | 90.8% | — | 29.9% | 72.17% | — | — | — | 1456 | — | — | — | 38.97% | 96.1% | 38.7% | 0.9% | 55.9% | — | — | 53.9 | 151.6 | — | — | — | 73.1% | — | — | 95.9% | 95.83% | — | — | 1481 | — | — | 53.5% | — | 6 | 76.0% | — | — | — | — | — | 1518 | — | — | 1782 | 1335 | — | — | — | 86.7% | — | — | — | — | — | — | — | — | — | — | — | 94.70% | 14.6% | 10.8% | — | — | 37.89% | — | — | — | — | 66.7% | — | 3.8% | 27% | — | 47.6% | — |
Scores are not normalised across benchmarks. Each column uses its own metric. Compare columns independently.