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DeepSeek R1 Distill Qwen 1.5B vs Llama 3.1 70B Instruct

Llama 3.1 70B Instruct leads the LLM Stats Score 7.7 to -2.8.

DeepSeek · Meta · Updated for 2026

Which is better?

Llama 3.1 70B Instruct leads the overall LLM Stats Score 7.7 to -2.8, ranking #276 overall.

In the 1 individual benchmarks reported for both models, Llama 3.1 70B Instruct 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 Distill Qwen 1.5B

  • you want the most recent training data — it shipped Jan 2025

Choose Llama 3.1 70B Instruct

  • overall performance matters — it scores 7.7 and ranks #276 on LLM Stats
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

At a glance

The differences that matter most.

Core performance indexes
-2.8
#330
7.7
#276
-2.4
#319
6.4
#276
-4.5
#250
3.7
#207
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
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
DeepSeek R1 Distill Qwen 1.5B
Llama 3.1 70B Instruct
5.7#262
11.8#234
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Distill Qwen 1.5B · 18 for Llama 3.1 70B Instruct

1 shared

DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Llama 3.1 70B Instruct is better at 1 benchmark (GPQA).

Llama 3.1 70B Instruct significantly outperforms across most benchmarks.

Sat Sep 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

68.2B diff

Llama 3.1 70B Instruct has 68.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 3832.6% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
Meta
Llama 3.1 70B Instruct
70.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
70.0B
Llama 3.1 70B Instruct

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).

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input- tokens
Output- tokens
Meta
Llama 3.1 70B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Sep 05 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, 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.

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

Llama 3.1 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Llama 3.1 70B Instruct was released on 2024-07-23.

DeepSeek R1 Distill Qwen 1.5B is 6 months newer than Llama 3.1 70B Instruct.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.6 years ago

6mo newer
Llama 3.1 70B Instruct

Jul 23, 2024

2.1 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 Qwen 1.5B and Llama 3.1 70B Instruct side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 1.5B
✓ Preferred
Llama 3.1 70B Instruct
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs Llama 3.1 70B Instruct.

Which is better, DeepSeek R1 Distill Qwen 1.5B or Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct leads the LLM Stats Score 7.7 to -2.8. DeepSeek R1 Distill Qwen 1.5B is made by DeepSeek 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 DeepSeek R1 Distill Qwen 1.5B compare to Llama 3.1 70B Instruct in benchmarks?

DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. 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 DeepSeek R1 Distill Qwen 1.5B and Llama 3.1 70B Instruct?

DeepSeek R1 Distill Qwen 1.5B 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 DeepSeek R1 Distill Qwen 1.5B and Llama 3.1 70B Instruct?

Key differences include LLM Stats Score (-2.8 vs 7.7), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Qwen 1.5B and Llama 3.1 70B Instruct?

DeepSeek R1 Distill Qwen 1.5B is developed by DeepSeek and Llama 3.1 70B Instruct is developed by Meta.