Model Comparison

DeepSeek-V3 vs Llama 3.2 90B InstructWhich is better in 2026?

DeepSeek-V3 significantly outperforms across most benchmarks. Llama 3.2 90B Instruct is 1.3x cheaper per token.

Verdict: DeepSeek-V3 vs Llama 3.2 90B Instruct — which is better?

DeepSeek-V3 (by DeepSeek) and Llama 3.2 90B Instruct (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V3 outperforms in 2 benchmarks (GPQA, MMLU), while Llama 3.2 90B Instruct is better at 0 benchmarks. DeepSeek-V3 significantly outperforms across most benchmarks.

On price, Llama 3.2 90B Instruct is roughly 1.3x 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.

Choose DeepSeek-V3 if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • 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 90B Instruct if…

  • cost matters — it's about 1.3x cheaper per token
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3 outperforms in 2 benchmarks (GPQA, MMLU), while Llama 3.2 90B Instruct is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.2 90B Instruct costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 1.3x cheaper than Llama 3.2 90B Instruct ($0.35/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 2.8x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than Llama 3.2 90B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

581.0B diff

DeepSeek-V3 has 581.0B more parameters than Llama 3.2 90B Instruct, making it 645.6% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Meta
Llama 3.2 90B Instruct
90.0Bparameters
671.0B
DeepSeek-V3
90.0B
Llama 3.2 90B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Llama 3.2 90B Instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Jun 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 90B Instruct supports multimodal inputs, whereas DeepSeek-V3 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-V3

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

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

MIT + Model License (Commercial use allowed)

Open weights

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Llama 3.2 90B Instruct was released on 2024-09-25.

DeepSeek-V3 is 3 months newer than Llama 3.2 90B Instruct.

DeepSeek-V3

Dec 25, 2024

1.5 years ago

3mo newer
Llama 3.2 90B Instruct

Sep 25, 2024

1.7 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 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Llama 3.2 90B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Less expensive input tokens
Higher GPQA score (59.1% vs 46.7%)
Higher MMLU score (88.5% vs 86.0%)
Meta
Supports multimodal inputs
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Meta
Llama 3.2 90B Instruct

FAQ

Common questions about DeepSeek-V3 vs Llama 3.2 90B Instruct.

Which is better, DeepSeek-V3 or Llama 3.2 90B Instruct?

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Llama 3.2 90B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3 compare to Llama 3.2 90B 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 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.

Is DeepSeek-V3 cheaper than Llama 3.2 90B Instruct?

DeepSeek-V3 is 1.3x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Llama 3.2 90B Instruct costs $0.35/M input and $0.40/M output via deepinfra.

What are the context window sizes for DeepSeek-V3 and Llama 3.2 90B Instruct?

DeepSeek-V3 supports 131K 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-V3 and Llama 3.2 90B Instruct?

Key differences include context window (131K vs 128K), input pricing ($0.27 vs $0.35/M), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Llama 3.2 90B Instruct?

DeepSeek-V3 is developed by DeepSeek and Llama 3.2 90B Instruct is developed by Meta.

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