Kimi K2 Instruct vs o1-mini
Kimi K2 Instruct leads the LLM Stats Score 21.9 to 10.0. Kimi K2 Instruct is 10.5x cheaper per token.
Moonshot AI · OpenAI · Updated for 2026
Which is better?
Kimi K2 Instruct leads the overall LLM Stats Score 21.9 to 10.0, ranking #181 overall.
In the 4 individual benchmarks reported for both models, Kimi K2 Instruct wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Kimi K2 Instruct is roughly 10.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2 Instruct also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Kimi K2 Instruct
- overall performance matters — it scores 21.9 and ranks #181 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- cost matters — it's about 10.5x cheaper per token
- you process long inputs — it offers a 200,000 token context window
- you want the most recent training data — it shipped Jul 2025
- you need open weights you can self-host or fine-tune
Choose o1-mini
- you want predictable pricing at $3.00/M input and $12.00/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
38 reported for Kimi K2 Instruct · 6 for o1-mini
Kimi K2 Instruct outperforms in 4 benchmarks (GPQA, HumanEval, MATH-500, MMLU), while o1-mini is better at 0 benchmarks.
Kimi K2 Instruct significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2 Instruct ($0.50/1M tokens) is 6.0x cheaper than o1-mini ($3.00/1M tokens).
For output processing, Kimi K2 Instruct ($0.50/1M tokens) is 24.0x cheaper than o1-mini ($12.00/1M tokens).
In conclusion, o1-mini is more expensive than Kimi K2 Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Kimi K2 Instruct accepts 200,000 input tokens compared to o1-mini's 128,000 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while o1-mini is limited to 65,536 tokens.
License
Usage and distribution terms
Kimi K2 Instruct is licensed under MIT, while o1-mini uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Kimi K2 Instruct was released on 2025-07-11, while o1-mini was released on 2024-09-12.
Kimi K2 Instruct is 10 months newer than o1-mini.
Jul 11, 2025
1.2 years ago
10mo newerSep 12, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2 Instruct is available from Fireworks, Novita. o1-mini is available from OpenAI, Azure.
Kimi K2 Instruct
o1-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2 Instruct and o1-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2 Instruct vs o1-mini.