GPT-4.1 Turbo vs Kimi K2 Instruct: which model should you choose?
We compared GPT-4.1 Turbo and Kimi K2 Instruct on price, context window and 12 benchmarks. GPT-4.1 Turbo has the stronger average benchmark score; Kimi K2 Instruct is cheaper on a blended 3:1 basis.
GPT-4.1 Turbo
GPT-4.1 Turbo is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $16.12 per million input tokens and $69.91 per million output tokens, and averages 82.9 across the index's benchmark suite.
- Input
- $16.12 / 1M
- Output
- $69.91 / 1M
- Context
- 1,000,000
- Avg score
- 82.9
- Open weights
- No
Kimi K2 Instruct
Kimi K2 Instruct is a multimodal model from Moonshot AI. It offers a 1,000,000-token context window, costs $5.80 per million input tokens and $23.99 per million output tokens, and averages 82.3 across the index's benchmark suite.
- Input
- $5.80 / 1M
- Output
- $23.99 / 1M
- Context
- 1,000,000
- Avg score
- 82.3
- Open weights
- Yes
Specification comparison
| Spec | GPT-4.1 Turbo | Kimi K2 Instruct | Edge |
|---|---|---|---|
| Input price / 1M | $16.12 | $5.80 | B |
| Output price / 1M | $69.91 | $23.99 | B |
| Context window | 1,000,000 | 1,000,000 | Tie |
| Max output | 128,000 | 65,536 | A |
| Average score | 82.9 | 82.3 | A |
| Arena Elo | 1446.2 | 1458.6 | B |
| Open weights | No | Yes | B |
Benchmark comparison
GPT-4.1 Turbo wins 6, Kimi K2 Instruct wins 6, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-4.1 Turbo | Kimi K2 Instruct | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.6 | 86.5 | 1.9 | Kimi K2 Instruct |
| GPQA Diamond | 76.1 | 78.4 | 2.3 | Kimi K2 Instruct |
| SWE-bench Verified | 74.7 | 75.1 | 0.4 | Kimi K2 Instruct |
| HumanEval | 89.8 | 87.3 | 2.5 | GPT-4.1 Turbo |
| MATH-500 | 86.9 | 88.0 | 1.1 | Kimi K2 Instruct |
| AIME 2025 | 77.4 | 77.3 | 0.1 | GPT-4.1 Turbo |
| LiveCodeBench | 78.7 | 74.1 | 4.6 | GPT-4.1 Turbo |
| IFEval | 88.2 | 87.5 | 0.7 | GPT-4.1 Turbo |
| TruthfulQA | 87.0 | 82.8 | 4.2 | GPT-4.1 Turbo |
| HellaSwag | 90.0 | 90.2 | 0.2 | Kimi K2 Instruct |
| MMMU | 78.5 | 78.3 | 0.2 | GPT-4.1 Turbo |
| Arena Elo | 1446.2 | 1458.6 | 12.4 | Kimi K2 Instruct |
Price analysis
On a blended 3:1 input-to-output basis, GPT-4.1 Turbo costs about $29.57 per million tokens and Kimi K2 Instruct costs about $10.35. Kimi K2 Instruct is roughly 65% cheaper than GPT-4.1 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 1,000,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GPT-4.1 Turbo wins 6, Kimi K2 Instruct wins 6, and 0 are tied. On the index average, GPT-4.1 Turbo leads Kimi K2 Instruct by 0.6 points (82.9 versus 82.3).
The price picture favours Kimi K2 Instruct. The context picture is effectively a tie. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with GPT-4.1 Turbo for quality-sensitive work and Kimi K2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose GPT-4.1 Turbo if
- You want the higher average benchmark score in this index.
- You need the larger 128,000-token output limit.
Choose Kimi K2 Instruct if
- Unit cost matters and you want the cheaper blended price.
- You need open weights for self-hosting or fine-tuning.
FAQ
Is GPT-4.1 Turbo better than Kimi K2 Instruct?
On the index average, GPT-4.1 Turbo leads Kimi K2 Instruct by 0.6 points (82.9 versus 82.3). The better choice depends on price, context and your task. GPT-4.1 Turbo wins 6 benchmarks, Kimi K2 Instruct wins 6.
Which is cheaper, GPT-4.1 Turbo or Kimi K2 Instruct?
Kimi K2 Instruct is cheaper on a blended 3:1 basis at about $10.35 per million tokens, versus $29.57 for GPT-4.1 Turbo.
Which has the larger context window?
Both models list a 1,000,000-token context window.
Are these models open weights?
GPT-4.1 Turbo is proprietary; Kimi K2 Instruct is open weights.
Which should I choose for production?
If you need a single default, start with GPT-4.1 Turbo for quality-sensitive work and Kimi K2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.