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. | 70B | 48B |
| 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. | $0.10DeepInfra | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.32DeepInfra | — |
| Overview | ||
| Company | Meta | Moonshot AI |
| Release date | Dec 6 2024 | Oct 30 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
LLaMA 3.3vsClaude Haiku 5.5Kimi LinearvsClaude Haiku 5.5LLaMA 3.3vsGPT-6.1 SolKimi LinearvsGPT-6.1 SolLLaMA 3.3vsGemini 4 ArgonKimi LinearvsGemini 4 ArgonLLaMA 3.3vsGrok 4.7Kimi LinearvsGrok 4.7LLaMA 3.3vsDeepSeek-V4.1-FlashKimi LinearvsDeepSeek-V4.1-FlashLLaMA 3.3vsMistral Large 4Kimi LinearvsMistral Large 4Frequently asked questions
LLaMA 3.3 and Kimi Linear don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 3.3 shipped 328 days before Kimi Linear, so benchmark comparisons should account for the intervening progress.
LLaMA 3.3 has 70B parameters, while Kimi Linear has 48B.
Direct benchmark comparisons are unavailable — LLaMA 3.3 and Kimi Linear don't publish scores on any of the same benchmarks.