DeepSeek R1 Distill Qwen 32B vs Llama 3.2 90B Instruct
DeepSeek R1 Distill Qwen 32B leads the LLM Stats Score 13.1 to 5.2. DeepSeek R1 Distill Qwen 32B is 2.7x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek R1 Distill Qwen 32B leads the overall LLM Stats Score 13.1 to 5.2, ranking #248 overall.
In the 1 individual benchmarks reported for both models, DeepSeek R1 Distill Qwen 32B wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek R1 Distill Qwen 32B is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Qwen 32B
- overall performance matters — it scores 13.1 and ranks #248 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
- cost matters — it's about 2.7x cheaper per token
- you want the most recent training data — it shipped Jan 2025
Choose Llama 3.2 90B Instruct
- you want predictable pricing at $0.35/M input and $0.40/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
4 reported for DeepSeek R1 Distill Qwen 32B · 13 for Llama 3.2 90B Instruct
DeepSeek R1 Distill Qwen 32B outperforms in 1 benchmarks (GPQA), while Llama 3.2 90B Instruct is better at 0 benchmarks.
DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Qwen 32B ($0.12/1M tokens) is 2.9x cheaper than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 2.2x cheaper than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, Llama 3.2 90B Instruct is more expensive than DeepSeek R1 Distill Qwen 32B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 3.2 90B Instruct has 57.2B more parameters than DeepSeek R1 Distill Qwen 32B, making it 174.4% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Llama 3.2 90B Instruct supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 32B 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 32B
Llama 3.2 90B Instruct
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 32B 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.
MIT
Open weights
Llama 3.2
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 32B was released on 2025-01-20, while Llama 3.2 90B Instruct was released on 2024-09-25.
DeepSeek R1 Distill Qwen 32B is 4 months newer than Llama 3.2 90B Instruct.
Jan 20, 2025
1.7 years ago
3mo newerSep 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.
Provider Availability
DeepSeek R1 Distill Qwen 32B is available from DeepInfra. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.
DeepSeek R1 Distill Qwen 32B
Llama 3.2 90B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 32B and Llama 3.2 90B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 32B vs Llama 3.2 90B Instruct.