Compare AI models
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 1T | 30B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 256k | — |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.60Google | $0.05Novita |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $2.50Google | $0.20Novita |
These models have no shared benchmark scores. | ||
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. | — | 28% |
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. | 71.3% | — |
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 68.3% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 73% |
| Overview | ||
| Company | Moonshot AI | NVIDIA |
| Release date | Nov 6 2025 | Dec 15 2025 |
| Access | Open Weight | Open Source |
| Model details | View model | View model |
Other comparisons
Kimi K2 ThinkingvsClaude Haiku 5.5Nemotron 3 NanovsClaude Haiku 5.5Kimi K2 ThinkingvsGPT-6.1 SolNemotron 3 NanovsGPT-6.1 SolKimi K2 ThinkingvsGemini 4 ArgonNemotron 3 NanovsGemini 4 ArgonKimi K2 ThinkingvsMuse Spark 1.3Nemotron 3 NanovsMuse Spark 1.3Kimi K2 ThinkingvsGrok 4.7Nemotron 3 NanovsGrok 4.7Kimi K2 ThinkingvsDeepSeek-V4.1-FlashNemotron 3 NanovsDeepSeek-V4.1-FlashFrequently asked questions
Kimi K2 Thinking and Nemotron 3 Nano don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Kimi K2 Thinking shipped 39 days before Nemotron 3 Nano, so benchmark comparisons should account for the intervening progress.
Kimi K2 Thinking has 1T parameters, while Nemotron 3 Nano has 30B. Kimi K2 Thinking is open weight, while Nemotron 3 Nano is open source.
Direct benchmark comparisons are unavailable — Kimi K2 Thinking and Nemotron 3 Nano don't publish scores on any of the same benchmarks.