DeepSeek R1 Distill Llama 70B vs Llama 3.2 3B Instruct
DeepSeek R1 Distill Llama 70B leads the LLM Stats Score 14.5 to -6.1. Llama 3.2 3B Instruct is 14.0x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek R1 Distill Llama 70B leads the overall LLM Stats Score 14.5 to -6.1, ranking #234 overall.
In the 1 individual benchmarks reported for both models, DeepSeek R1 Distill Llama 70B wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 3.2 3B Instruct is roughly 14.0x 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 Llama 70B
- overall performance matters — it scores 14.5 and ranks #234 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 3.2 3B Instruct
- cost matters — it's about 14.0x cheaper per token
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 Llama 70B · 15 for Llama 3.2 3B Instruct
DeepSeek R1 Distill Llama 70B outperforms in 1 benchmarks (GPQA), while Llama 3.2 3B Instruct is better at 0 benchmarks.
DeepSeek R1 Distill Llama 70B 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 Llama 70B ($0.10/1M tokens) is 10.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).
For output processing, DeepSeek R1 Distill Llama 70B ($0.40/1M tokens) is 20.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).
In conclusion, DeepSeek R1 Distill Llama 70B is more expensive than Llama 3.2 3B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek R1 Distill Llama 70B has 67.4B more parameters than Llama 3.2 3B Instruct, making it 2099.4% 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.
License
Usage and distribution terms
DeepSeek R1 Distill Llama 70B is licensed under MIT, while Llama 3.2 3B Instruct uses Llama 3.2 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.2 Community License
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Llama 3.2 3B Instruct was released on 2024-09-25.
DeepSeek R1 Distill Llama 70B is 4 months newer than Llama 3.2 3B Instruct.
Jan 20, 2025
1.6 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 Llama 70B is available from DeepInfra. Llama 3.2 3B Instruct is available from DeepInfra.
DeepSeek R1 Distill Llama 70B
Llama 3.2 3B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Llama 70B and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Llama 70B vs Llama 3.2 3B Instruct.