The AI arena is free today

Open Superagent

DeepSeek R1 Distill Qwen 1.5B vs Llama 3.2 90B Instruct

DeepSeek R1 Distill Qwen 1.5B and Llama 3.2 90B Instruct are closely matched at -3.0 and 5.2 on the LLM Stats Score.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek R1 Distill Qwen 1.5B and Llama 3.2 90B Instruct are closely matched on the overall LLM Stats Score at -3.0 and 5.2.

In the 1 individual benchmarks reported for both models, Llama 3.2 90B 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 3.2 90B Instruct

  • 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
-3.0
#345
5.2
#300
-2.6
#335
6.7
#288
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
— / M
$0.35 / M
Output price
— / M
$0.40 / 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 3.2 90B Instruct
5.4#271
11.6#238
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Distill Qwen 1.5B · 13 for Llama 3.2 90B Instruct

1 shared

DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Llama 3.2 90B Instruct is better at 1 benchmark (GPQA).

Llama 3.2 90B Instruct significantly outperforms across most benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

88.2B diff

Llama 3.2 90B Instruct has 88.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 4956.2% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
Meta
Llama 3.2 90B Instruct
90.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
90.0B
Llama 3.2 90B Instruct

Context Window

Maximum input and output token capacity

Only Llama 3.2 90B Instruct specifies input context (128,000 tokens). Only Llama 3.2 90B Instruct specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input- tokens
Output- tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Llama 3.2 90B Instruct supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.

Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Qwen 1.5B

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while Llama 3.2 90B Instruct uses Llama 3.2.

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 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Llama 3.2 90B Instruct was released on 2024-09-25.

DeepSeek R1 Distill Qwen 1.5B is 4 months newer than Llama 3.2 90B Instruct.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.7 years ago

3mo newer
Llama 3.2 90B Instruct

Sep 25, 2024

2.0 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 3.2 90B Instruct side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 1.5B
✓ Preferred
Llama 3.2 90B Instruct
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs Llama 3.2 90B Instruct.

Which is better, DeepSeek R1 Distill Qwen 1.5B or Llama 3.2 90B Instruct?

DeepSeek R1 Distill Qwen 1.5B and Llama 3.2 90B Instruct are closely matched on the LLM Stats Score at -3.0 and 5.2. DeepSeek R1 Distill Qwen 1.5B is made by DeepSeek and Llama 3.2 90B 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 3.2 90B 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 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.

What are the context window sizes for DeepSeek R1 Distill Qwen 1.5B and Llama 3.2 90B Instruct?

DeepSeek R1 Distill Qwen 1.5B supports an unknown number of tokens and Llama 3.2 90B 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 3.2 90B Instruct?

Key differences include LLM Stats Score (-3.0 vs 5.2), multimodal support (no vs yes), licensing (MIT vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Qwen 1.5B and Llama 3.2 90B Instruct?

DeepSeek R1 Distill Qwen 1.5B is developed by DeepSeek and Llama 3.2 90B Instruct is developed by Meta.