Model Comparison

DeepSeek R1 Distill Llama 70B vs Llama 3.2 3B Instruct

DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks. Llama 3.2 3B Instruct is 14.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

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.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.2 3B Instruct costs less

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Llama 70B
Input tokens$0.10
Output tokens$0.40
Best providerDeepinfra
Meta
Llama 3.2 3B Instruct
Input tokens$0.01
Output tokens$0.02
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

67.4B diff

DeepSeek R1 Distill Llama 70B has 67.4B more parameters than Llama 3.2 3B Instruct, making it 2099.4% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
Meta
Llama 3.2 3B Instruct
3.2Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
3.2B
Llama 3.2 3B Instruct

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.

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Meta
Llama 3.2 3B Instruct
Input128,000 tokens
Output128,000 tokens
Wed Apr 15 2026 • llm-stats.com

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.

DeepSeek R1 Distill Llama 70B

MIT

Open weights

Llama 3.2 3B Instruct

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.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.2 years ago

3mo newer
Llama 3.2 3B Instruct

Sep 25, 2024

1.6 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

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

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

Llama 3.2 3B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.01/1MOutput Price:Output: $0.02/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Higher GPQA score (65.2% vs 32.8%)
Meta
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Llama 70B
Meta
Llama 3.2 3B Instruct

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs Llama 3.2 3B Instruct

DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks. DeepSeek R1 Distill Llama 70B is made by DeepSeek and Llama 3.2 3B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. Llama 3.2 3B Instruct scores NIH/Multi-needle: 84.7%, ARC-C: 78.6%, GSM8k: 77.7%, IFEval: 77.4%, HellaSwag: 69.8%.
Llama 3.2 3B Instruct is 10.0x cheaper for input tokens. DeepSeek R1 Distill Llama 70B costs $0.10/M input and $0.40/M output via deepinfra. Llama 3.2 3B Instruct costs $0.01/M input and $0.02/M output via deepinfra.
DeepSeek R1 Distill Llama 70B supports 128K tokens and Llama 3.2 3B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($0.10 vs $0.01/M), licensing (MIT vs Llama 3.2 Community License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Distill Llama 70B is developed by DeepSeek and Llama 3.2 3B Instruct is developed by Meta.