Model Comparison

DeepSeek-V3.2-Speciale vs Llama 3.1 405B Instruct

Comparing DeepSeek-V3.2-Speciale and Llama 3.1 405B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Speciale and Llama 3.1 405B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2-Speciale costs less

For input processing, DeepSeek-V3.2-Speciale ($0.28/1M tokens) is 3.2x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).

For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 2.1x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).

In conclusion, Llama 3.1 405B Instruct is more expensive than DeepSeek-V3.2-Speciale.*

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

Lowest available price from all providers
Wed May 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Speciale
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Meta
Llama 3.1 405B Instruct
Input tokens$0.89
Output tokens$0.89
Best providerLambda
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

280.0B diff

DeepSeek-V3.2-Speciale has 280.0B more parameters than Llama 3.1 405B Instruct, making it 69.1% larger.

DeepSeek
DeepSeek-V3.2-Speciale
685.0Bparameters
Meta
Llama 3.1 405B Instruct
405.0Bparameters
685.0B
DeepSeek-V3.2-Speciale
405.0B
Llama 3.1 405B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V3.2-Speciale accepts 131,072 input tokens compared to Llama 3.1 405B Instruct's 128,000 tokens. DeepSeek-V3.2-Speciale can generate longer responses up to 131,072 tokens, while Llama 3.1 405B Instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
Meta
Llama 3.1 405B Instruct
Input128,000 tokens
Output128,000 tokens
Wed May 13 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Speciale is licensed under MIT, while Llama 3.1 405B Instruct uses Llama 3.1 Community License.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2-Speciale

MIT

Open weights

Llama 3.1 405B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while Llama 3.1 405B Instruct was released on 2024-07-23.

DeepSeek-V3.2-Speciale is 17 months newer than Llama 3.1 405B Instruct.

DeepSeek-V3.2-Speciale

Dec 1, 2025

5 months ago

1.4yr newer
Llama 3.1 405B Instruct

Jul 23, 2024

1.8 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-V3.2-Speciale is available from DeepSeek. Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate.

DeepSeek-V3.2-Speciale

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Llama 3.1 405B Instruct

lambda logo
Lambda
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
deepinfra logo
Deepinfra
Input Price:Input: $1.79/1MOutput Price:Output: $1.79/1M
fireworks logo
Fireworks
Input Price:Input: $3.00/1MOutput Price:Output: $3.00/1M
bedrock logo
AWS Bedrock
Input Price:Input: $3.00/1MOutput Price:Output: $3.00/1M
together logo
Together
Input Price:Input: $3.50/1MOutput Price:Output: $3.50/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $4.00/1MOutput Price:Output: $4.00/1M
google logo
Google
Input Price:Input: $5.00/1MOutput Price:Output: $16.00/1M
replicate logo
Replicate
Input Price:Input: $9.50/1MOutput Price:Output: $9.50/1M
* 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
Less expensive output tokens
Meta

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Speciale
Meta
Llama 3.1 405B Instruct

FAQ

Common questions about DeepSeek-V3.2-Speciale vs Llama 3.1 405B Instruct.

Which is better, DeepSeek-V3.2-Speciale or Llama 3.1 405B Instruct?

DeepSeek-V3.2-Speciale (DeepSeek) and Llama 3.1 405B Instruct (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V3.2-Speciale compare to Llama 3.1 405B Instruct in benchmarks?

DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. Llama 3.1 405B Instruct scores ARC-C: 96.9%, GSM8k: 96.8%, API-Bank: 92.0%, Multilingual MGSM (CoT): 91.6%, HumanEval: 89.0%.

Is DeepSeek-V3.2-Speciale cheaper than Llama 3.1 405B Instruct?

DeepSeek-V3.2-Speciale is 3.2x cheaper for input tokens. DeepSeek-V3.2-Speciale costs $0.28/M input and $0.42/M output via deepseek. Llama 3.1 405B Instruct costs $0.89/M input and $0.89/M output via lambda.

What are the context window sizes for DeepSeek-V3.2-Speciale and Llama 3.1 405B Instruct?

DeepSeek-V3.2-Speciale supports 131K tokens and Llama 3.1 405B 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-V3.2-Speciale and Llama 3.1 405B Instruct?

Key differences include context window (131K vs 128K), input pricing ($0.28 vs $0.89/M), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Speciale and Llama 3.1 405B Instruct?

DeepSeek-V3.2-Speciale is developed by DeepSeek and Llama 3.1 405B Instruct is developed by Meta.