DeepSeek-R1 vs Kimi K2 Instruct vs GPT-4.1

It is close. Our weighted score puts them within 2 points (GPT-4.1 52/100, Kimi K2 Instruct 50/100, DeepSeek-R1 48/100), so choose by what matters most for your work: Kimi K2 Instruct for raw capability and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Kimi K2 Instruct is cheaper at $0.57 input / $2.30 output per million tokens (median across 11 API providers). DeepSeek-R1 costs $0.70 input / $4.88 output per million tokens (median across 11 API providers); GPT-4.1 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for Kimi K2 Instruct versus $1.75 for DeepSeek-R1 (1.7× as much) and $3.50 for GPT-4.1 (3.5× as much).

Kimi K2 Instruct scores higher on the Capabilities Index (ECI): Kimi K2 Instruct 139.9 (#112 of 165), DeepSeek-R1 138.8 (#119 of 165) and GPT-4.1 136.7 (#125 of 165). The confidence ranges of the top two overlap (136.3–141.6 vs 136.5–140.2), so treat the gap as small.

There are no published SWE-bench Verified results for DeepSeek-R1 and Kimi K2 Instruct yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

GPT-4.1 has the largest context window at 1,047,576 tokens, against 131,072 for Kimi K2 Instruct and 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, Kimi K2 Instruct up to 32,768, GPT-4.1 up to 32,768 tokens.

DeepSeek-R1 accepts text; Kimi K2 Instruct accepts text; GPT-4.1 accepts text, images and PDFs. GPT-4.1 handles the widest range of inputs.

DeepSeek-R1 and Kimi K2 Instruct publishes its weights (Modified MIT) and can be self-hosted; GPT-4.1 is proprietary.

Kimi K2 Instruct is the newest, released Jul 11, 2025. GPT-4.1 came out Apr 14, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, GPT-4.1 Apr 2024.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.