Kimi K2 Instruct vs Llama 3.1 405B Instruct
Kimi K2 Instruct leads the LLM Stats Score 21.9 to 14.7. Kimi K2 Instruct is 1.8x cheaper per token.
Moonshot AI · Meta · Updated for 2026
Which is better?
Kimi K2 Instruct leads the overall LLM Stats Score 21.9 to 14.7, ranking #188 overall.
In the 6 individual benchmarks reported for both models, Kimi K2 Instruct wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, Kimi K2 Instruct is roughly 1.8x 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 #188 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 6 exact shared results
- cost matters — it's about 1.8x 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
Choose Llama 3.1 405B Instruct
- you want predictable pricing at $0.89/M input and $0.89/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 · 18 for Llama 3.1 405B Instruct
Kimi K2 Instruct outperforms in 6 benchmarks (GPQA, GSM8k, HumanEval, IFEval, MMLU, MMLU-Pro), while Llama 3.1 405B Instruct 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 1.8x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).
For output processing, Kimi K2 Instruct ($0.50/1M tokens) is 1.8x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).
In conclusion, Llama 3.1 405B Instruct is more expensive than Kimi K2 Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2 Instruct has 595.0B more parameters than Llama 3.1 405B Instruct, making it 146.9% larger.
Context Window
Maximum input and output token capacity
Kimi K2 Instruct accepts 200,000 input tokens compared to Llama 3.1 405B Instruct's 128,000 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while Llama 3.1 405B Instruct is limited to 128,000 tokens.
License
Usage and distribution terms
Kimi K2 Instruct is licensed under MIT, while Llama 3.1 405B Instruct uses Llama 3.1 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
Kimi K2 Instruct was released on 2025-07-11, while Llama 3.1 405B Instruct was released on 2024-07-23.
Kimi K2 Instruct is 12 months newer than Llama 3.1 405B Instruct.
Jul 11, 2025
1.2 years ago
11mo newerJul 23, 2024
2.2 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. Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate.
Kimi K2 Instruct
Llama 3.1 405B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2 Instruct and Llama 3.1 405B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2 Instruct vs Llama 3.1 405B Instruct.