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Kimi-k1.5 vs Llama 3.1 70B Instruct

Kimi-k1.5 leads the LLM Stats Score 17.2 to 7.6.

Moonshot AI · Meta · Updated for 2026

Which is better?

Kimi-k1.5 leads the overall LLM Stats Score 17.2 to 7.6, ranking #224 overall.

The models split the 2 individual benchmarks reported for both models evenly.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Kimi-k1.5

  • overall performance matters — it scores 17.2 and ranks #224 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jan 2025

Choose Llama 3.1 70B Instruct

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
17.2
#224
7.6
#292
16.4
#221
6.3
#294
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
— / M
$0.20 / M
Output price
— / M
$0.20 / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Kimi-k1.5
Llama 3.1 70B Instruct
20.2#161
11.4#241
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for Kimi-k1.5 · 18 for Llama 3.1 70B Instruct

2 shared

Kimi-k1.5 outperforms in 1 benchmarks (MMLU), while Llama 3.1 70B Instruct is better at 1 benchmark (IFEval).

Both models are evenly matched across the benchmarks.

Wed Sep 23 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Llama 3.1 70B Instruct specifies input context (128,000 tokens). Only Llama 3.1 70B Instruct specifies output context (128,000 tokens).

Moonshot AI
Kimi-k1.5
Input- tokens
Output- tokens
Meta
Llama 3.1 70B Instruct
Input128,000 tokens
Output128,000 tokens
Wed Sep 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Kimi-k1.5 supports multimodal inputs, whereas Llama 3.1 70B Instruct does not.

Kimi-k1.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi-k1.5

Text
Images
Audio
Video

Llama 3.1 70B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi-k1.5 is licensed under a proprietary license, while Llama 3.1 70B Instruct uses Llama 3.1 Community License.

License differences may affect how you can use these models in commercial or open-source projects.

Kimi-k1.5

Proprietary

Closed source

Llama 3.1 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

Kimi-k1.5 was released on 2025-01-20, while Llama 3.1 70B Instruct was released on 2024-07-23.

Kimi-k1.5 is 6 months newer than Llama 3.1 70B Instruct.

Kimi-k1.5

Jan 20, 2025

1.7 years ago

6mo newer
Llama 3.1 70B Instruct

Jul 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.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Kimi-k1.5 and Llama 3.1 70B Instruct side-by-side, then vote on the output you prefer.

Kimi-k1.5
✓ Preferred
Llama 3.1 70B Instruct
Open in Playground

FAQ

Common questions about Kimi-k1.5 vs Llama 3.1 70B Instruct.

Which is better, Kimi-k1.5 or Llama 3.1 70B Instruct?

Kimi-k1.5 leads the LLM Stats Score 17.2 to 7.6. Kimi-k1.5 is made by Moonshot AI and Llama 3.1 70B Instruct is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Kimi-k1.5 compare to Llama 3.1 70B Instruct in benchmarks?

Kimi-k1.5 scores MATH-500: 96.2%, CLUEWSC: 91.4%, C-Eval: 88.3%, MMLU: 87.4%, IFEval: 87.2%. Llama 3.1 70B Instruct scores GSM-8K (CoT): 95.1%, ARC-C: 94.8%, API-Bank: 90.0%, IFEval: 87.5%, Multilingual MGSM (CoT): 86.9%.

What are the context window sizes for Kimi-k1.5 and Llama 3.1 70B Instruct?

Kimi-k1.5 supports an unknown number of tokens and Llama 3.1 70B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Kimi-k1.5 and Llama 3.1 70B Instruct?

Key differences include LLM Stats Score (17.2 vs 7.6), multimodal support (yes vs no), licensing (Proprietary vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi-k1.5 and Llama 3.1 70B Instruct?

Kimi-k1.5 is developed by Moonshot AI and Llama 3.1 70B Instruct is developed by Meta.