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. | — | 48B |
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. | 100k | 1M |
| These models have no shared benchmark scores. | ||
HumanEvalFunction synthesis — 164 small Python problems: the AI is given a function's description and has to write the working function. This was the coding benchmark of the GPT-3.5 and GPT-4 era, before the field moved to fixing real bugs in real repositories. Higher is better. | 58.7% | — |
GSM8KGrade-school math — Grade-school maths word problems that take a few steps of arithmetic to work through. It separated the models of 2022 and 2023 sharply, then saturated. One caveat on the historical numbers: OpenAI included part of the GSM8K training set in GPT-4's pre-training mix, so GPT-4's score is not a clean few-shot result. Higher is better. | 86.7% | — |
| Overview | ||
| Company | Anthropic | Moonshot AI |
| Release date | Aug 9 2023 | Oct 30 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Claude Instant 1.2vsGPT-6.1 SolKimi LinearvsGPT-6.1 SolClaude Instant 1.2vsGemini 4 ArgonKimi LinearvsGemini 4 ArgonClaude Instant 1.2vsMuse Spark OpenKimi LinearvsMuse Spark OpenClaude Instant 1.2vsGrok 4.7Kimi LinearvsGrok 4.7Claude Instant 1.2vsDeepSeek-V4.1-Flash-1017Kimi LinearvsDeepSeek-V4.1-Flash-1017Claude Instant 1.2vsMistral Large 4Kimi LinearvsMistral Large 4Frequently asked questions
Claude Instant 1.2 and Kimi Linear don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Claude Instant 1.2 shipped 813 days before Kimi Linear, so benchmark comparisons should account for the intervening progress.
Context windows are 100k (Claude Instant 1.2) vs 1M (Kimi Linear). Claude Instant 1.2 is closed, while Kimi Linear is open weight.
Direct benchmark comparisons are unavailable — Claude Instant 1.2 and Kimi Linear don't publish scores on any of the same benchmarks.