DeepSeek-V3 vs Llama 3.2 3B Instruct

DeepSeek-V3 leads the LLM Stats Score 15.7 to -5.9. Llama 3.2 3B Instruct is 38.2x cheaper per token.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek-V3 leads the overall LLM Stats Score 15.7 to -5.9, ranking #216 overall.

In the 3 individual benchmarks reported for both models, DeepSeek-V3 wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, Llama 3.2 3B Instruct is roughly 38.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V3 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3

overall performance matters — it scores 15.7 and ranks #216 on LLM Stats
your work emphasizes reasoning — it leads those capability indexes
you value its reported benchmark strengths — it wins 3 of 3 exact shared results
you process long inputs — it offers a 131,072 token context window
you want the most recent training data — it shipped Dec 2024

Choose Llama 3.2 3B Instruct

cost matters — it's about 38.2x cheaper per token

At a glance

The differences that matter most.

Better token value: Llama 3.2 3B Instruct

DeepSeek-V3

DeepSeek

Llama 3.2 3B Instruct

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared

Index

DeepSeek-V3

Llama 3.2 3B Instruct

Math

18.2#175 · 7 evals

-3.3#304 · 4 evals

Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V3 · 15 for Llama 3.2 3B Instruct

3 shared

DeepSeek-V3 outperforms in 3 benchmarks (GPQA, IFEval, MMLU), while Llama 3.2 3B Instruct is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Fri Sep 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Llama 3.2 3B Instruct costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 27.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 55.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).

In conclusion, DeepSeek-V3 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

Fri Sep 04 2026 • llm-stats.com

DeepSeek-V3

Input tokens$0.27

Output tokens$1.10

Best providerDeepSeek

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

667.8B diff

DeepSeek-V3 has 667.8B more parameters than Llama 3.2 3B Instruct, making it 20803.4% larger.

DeepSeek-V3

671.0Bparameters

Llama 3.2 3B Instruct

3.2Bparameters

671.0B

DeepSeek-V3

3.2B

Llama 3.2 3B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Llama 3.2 3B Instruct's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Llama 3.2 3B Instruct is limited to 128,000 tokens.

DeepSeek-V3

Input131,072 tokens

Output131,072 tokens

Llama 3.2 3B Instruct

Input128,000 tokens

Output128,000 tokens

Fri Sep 04 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), 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-V3

MIT + Model License (Commercial use allowed)

Open weights

Llama 3.2 3B Instruct

Llama 3.2 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Llama 3.2 3B Instruct was released on 2024-09-25.

DeepSeek-V3 is 3 months newer than Llama 3.2 3B Instruct.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

3mo newer

Llama 3.2 3B Instruct

Sep 25, 2024

1.9 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-V3 is available from DeepSeek. Llama 3.2 3B Instruct is available from DeepInfra.

DeepSeek-V3

DeepSeek

Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Llama 3.2 3B Instruct

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→

Judge for yourself.

Run your own prompts against DeepSeek-V3 and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V3

✓ Preferred

Llama 3.2 3B Instruct

Open in Playground

FAQ

Common questions about DeepSeek-V3 vs Llama 3.2 3B Instruct.

Which is better, DeepSeek-V3 or Llama 3.2 3B Instruct?

DeepSeek-V3 leads the LLM Stats Score 15.7 to -5.9. DeepSeek-V3 is made by DeepSeek and Llama 3.2 3B 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-V3 compare to Llama 3.2 3B Instruct in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Llama 3.2 3B Instruct scores NIH/Multi-needle: 84.7%, ARC-C: 78.6%, GSM8k: 77.7%, IFEval: 77.4%, HellaSwag: 69.8%.

Is DeepSeek-V3 cheaper than Llama 3.2 3B Instruct?

Llama 3.2 3B Instruct is 27.0x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Llama 3.2 3B Instruct costs $0.01/M input and $0.02/M output via deepinfra.

What are the context window sizes for DeepSeek-V3 and Llama 3.2 3B Instruct?

DeepSeek-V3 supports 131K 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.

What are the main differences between DeepSeek-V3 and Llama 3.2 3B Instruct?

Key differences include LLM Stats Score (15.7 vs -5.9), context window (131K vs 128K), input pricing ($0.27 vs $0.01/M), licensing (MIT + Model License (Commercial use allowed) vs Llama 3.2 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Llama 3.2 3B Instruct?

DeepSeek-V3 is developed by DeepSeek and Llama 3.2 3B Instruct is developed by Meta.

DeepSeek-V3 vs Llama 3.2 3B Instruct