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DeepSeek R1 Distill Llama 70B vs Kimi-k1.5

DeepSeek R1 Distill Llama 70B and Kimi-k1.5 are closely matched at 14.8 and 17.5 on the LLM Stats Score.

DeepSeek · Moonshot AI · Updated for 2026

Which is better?

DeepSeek R1 Distill Llama 70B and Kimi-k1.5 are closely matched on the overall LLM Stats Score at 14.8 and 17.5.

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 DeepSeek R1 Distill Llama 70B

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

Choose Kimi-k1.5

  • you are already invested in the Moonshot AI ecosystem

At a glance

The differences that matter most.

Core performance indexes
14.8
#214
17.5
#196
15.0
#208
16.8
#195
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Distill Llama 70B
Kimi-k1.5
16.7#191
20.6#144
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Distill Llama 70B · 9 for Kimi-k1.5

2 shared

DeepSeek R1 Distill Llama 70B outperforms in 1 benchmarks (AIME 2024), while Kimi-k1.5 is better at 1 benchmark (MATH-500).

Both models are evenly matched across the benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Llama 70B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Moonshot AI
Kimi-k1.5
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Kimi-k1.5 supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.

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

DeepSeek R1 Distill Llama 70B

Text
Images
Audio
Video

Kimi-k1.5

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Llama 70B is licensed under MIT, while Kimi-k1.5 uses a proprietary license.

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

DeepSeek R1 Distill Llama 70B

MIT

Open weights

Kimi-k1.5

Proprietary

Closed source

Release Timeline

When each model was launched

Both models were released on 2025-01-20.

They likely represent similar generations of model development.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.6 years ago

Kimi-k1.5

Jan 20, 2025

1.6 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 DeepSeek R1 Distill Llama 70B and Kimi-k1.5 side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Llama 70B
✓ Preferred
Kimi-k1.5
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs Kimi-k1.5.

Which is better, DeepSeek R1 Distill Llama 70B or Kimi-k1.5?

DeepSeek R1 Distill Llama 70B and Kimi-k1.5 are closely matched on the LLM Stats Score at 14.8 and 17.5. DeepSeek R1 Distill Llama 70B is made by DeepSeek and Kimi-k1.5 is made by Moonshot AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek R1 Distill Llama 70B compare to Kimi-k1.5 in benchmarks?

DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. Kimi-k1.5 scores MATH-500: 96.2%, CLUEWSC: 91.4%, C-Eval: 88.3%, MMLU: 87.4%, IFEval: 87.2%.

What are the context window sizes for DeepSeek R1 Distill Llama 70B and Kimi-k1.5?

DeepSeek R1 Distill Llama 70B supports 128K tokens and Kimi-k1.5 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek R1 Distill Llama 70B and Kimi-k1.5?

Key differences include LLM Stats Score (14.8 vs 17.5), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Llama 70B and Kimi-k1.5?

DeepSeek R1 Distill Llama 70B is developed by DeepSeek and Kimi-k1.5 is developed by Moonshot AI.