Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | — | 72B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 1M | 128k |
| Benchmarks | ||
SWE-Bench VerifiedCoding — Real 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. | 76.2% | 60.4% |
BullshitBench v2Nonsense detection — Given 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. | 48% | — |
Next.js EvalsNext.js coding — Vercel'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. | 52% | — |
ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | 31.1% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 91.9% | — |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | 81% | — |
| Overview | ||
| Company | Moonshot AI | |
| Release date | Nov 18 2025 | Jun 17 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 3.0 ProvsClaude Haiku 5.5Kimi-DevvsClaude Haiku 5.5Gemini 3.0 ProvsGPT-6.1 SolKimi-DevvsGPT-6.1 SolGemini 3.0 ProvsMuse Spark OpenKimi-DevvsMuse Spark OpenGemini 3.0 ProvsGrok 4.7Kimi-DevvsGrok 4.7Gemini 3.0 ProvsDeepSeek-V4.1-Flash-1017Kimi-DevvsDeepSeek-V4.1-Flash-1017Gemini 3.0 ProvsMistral Large 4Kimi-DevvsMistral Large 4Frequently asked questions
Gemini 3.0 Pro leads Kimi-Dev on 1 of the 1 benchmark they both report (SWE-Bench Verified). Kimi-Dev shipped 154 days before Gemini 3.0 Pro, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Gemini 3.0 Pro) vs 128k (Kimi-Dev). Gemini 3.0 Pro is closed, while Kimi-Dev is open weight.
On SWE-Bench Verified, Gemini 3.0 Pro leads at 76.2% vs Kimi-Dev at 60.4%.