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DeepSeek R1 Zero vs Llama 3.1 8B Instruct

DeepSeek R1 Zero leads the LLM Stats Score 16.2 to -2.4.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek R1 Zero leads the overall LLM Stats Score 16.2 to -2.4, ranking #208 overall.

In the 1 individual benchmarks reported for both models, DeepSeek R1 Zero wins 1; this is a narrower head-to-head signal than the composite indexes.

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

Choose DeepSeek R1 Zero

  • overall performance matters — it scores 16.2 and ranks #208 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Jan 2025

Choose Llama 3.1 8B Instruct

  • you want predictable pricing at $0.03/M input and $0.03/M output

At a glance

The differences that matter most.

Core performance indexes
16.2
#208
-2.4
#322
16.5
#200
-3.5
#321
4.4
#196
-2.2
#235
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$0.03 / M
Output price
— / M
$0.03 / M
Context window
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Zero
Llama 3.1 8B Instruct
17.7#185
-2.1#300
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Zero · 18 for Llama 3.1 8B Instruct

1 shared

DeepSeek R1 Zero outperforms in 1 benchmarks (GPQA), while Llama 3.1 8B Instruct is better at 0 benchmarks.

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Mon Aug 31 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

663.0B diff

DeepSeek R1 Zero has 663.0B more parameters than Llama 3.1 8B Instruct, making it 8287.5% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Meta
Llama 3.1 8B Instruct
8.0Bparameters
671.0B
DeepSeek R1 Zero
8.0B
Llama 3.1 8B Instruct

Context Window

Maximum input and output token capacity

Only Llama 3.1 8B Instruct specifies input context (131,072 tokens). Only Llama 3.1 8B Instruct specifies output context (131,072 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Meta
Llama 3.1 8B Instruct
Input131,072 tokens
Output131,072 tokens
Mon Aug 31 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Llama 3.1 8B Instruct uses Llama 3.1 Community License.

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

DeepSeek R1 Zero

MIT

Open weights

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Llama 3.1 8B Instruct was released on 2024-07-23.

DeepSeek R1 Zero is 6 months newer than Llama 3.1 8B Instruct.

DeepSeek R1 Zero

Jan 20, 2025

1.6 years ago

6mo newer
Llama 3.1 8B Instruct

Jul 23, 2024

2.1 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while DeepSeek R1 Zero's cutoff date is not specified.

We can confirm Llama 3.1 8B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek R1 Zero's cutoff date.

DeepSeek R1 Zero

Llama 3.1 8B Instruct

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek R1 Zero and Llama 3.1 8B Instruct side-by-side, then vote on the output you prefer.

DeepSeek R1 Zero
✓ Preferred
Llama 3.1 8B Instruct
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs Llama 3.1 8B Instruct.

Which is better, DeepSeek R1 Zero or Llama 3.1 8B Instruct?

DeepSeek R1 Zero leads the LLM Stats Score 16.2 to -2.4. DeepSeek R1 Zero is made by DeepSeek and Llama 3.1 8B 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 DeepSeek R1 Zero compare to Llama 3.1 8B Instruct in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Llama 3.1 8B Instruct scores GSM-8K (CoT): 84.5%, ARC-C: 83.4%, API-Bank: 82.6%, IFEval: 80.4%, BFCL: 76.1%.

What are the context window sizes for DeepSeek R1 Zero and Llama 3.1 8B Instruct?

DeepSeek R1 Zero supports an unknown number of tokens and Llama 3.1 8B Instruct supports 131K 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 Zero and Llama 3.1 8B Instruct?

Key differences include LLM Stats Score (16.2 vs -2.4), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Llama 3.1 8B Instruct?

DeepSeek R1 Zero is developed by DeepSeek and Llama 3.1 8B Instruct is developed by Meta.