Model Comparison

DeepSeek-V3.2-Exp vs Llama 3.1 8B Instruct

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. Llama 3.1 8B Instruct is 10.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2-Exp outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Llama 3.1 8B Instruct is better at 0 benchmarks.

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Sun Apr 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.1 8B Instruct costs less

For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 9.0x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 13.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

In conclusion, DeepSeek-V3.2-Exp is more expensive than Llama 3.1 8B Instruct.*

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

Lowest available price from all providers
Sun Apr 19 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Meta
Llama 3.1 8B Instruct
Input tokens$0.03
Output tokens$0.03
Best providerLambda
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

677.0B diff

DeepSeek-V3.2-Exp has 677.0B more parameters than Llama 3.1 8B Instruct, making it 8462.5% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Meta
Llama 3.1 8B Instruct
8.0Bparameters
685.0B
DeepSeek-V3.2-Exp
8.0B
Llama 3.1 8B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V3.2-Exp accepts 163,840 input tokens compared to Llama 3.1 8B Instruct's 131,072 tokens. Llama 3.1 8B Instruct can generate longer responses up to 131,072 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Meta
Llama 3.1 8B Instruct
Input131,072 tokens
Output131,072 tokens
Sun Apr 19 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, while Llama 3.1 8B 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-Exp

MIT

Open weights

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Llama 3.1 8B Instruct was released on 2024-07-23.

DeepSeek-V3.2-Exp is 14 months newer than Llama 3.1 8B Instruct.

DeepSeek-V3.2-Exp

Sep 29, 2025

6 months ago

1.2yr newer
Llama 3.1 8B Instruct

Jul 23, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while DeepSeek-V3.2-Exp's cutoff date is not specified.

We can confirm Llama 3.1 8B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek-V3.2-Exp's cutoff date.

DeepSeek-V3.2-Exp

—

Llama 3.1 8B Instruct

Dec 2023

Provider Availability

DeepSeek-V3.2-Exp is available from Novita. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.

DeepSeek-V3.2-Exp

novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $0.41/1M

Llama 3.1 8B Instruct

lambda logo
Lambda
Input Price:Input: $0.03/1MOutput Price:Output: $0.03/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M
groq logo
Groq
Input Price:Input: $0.05/1MOutput Price:Output: $0.08/1M
sambanova logo
Sambanova
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
together logo
Together
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.22/1MOutput Price:Output: $0.22/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Higher GPQA score (79.9% vs 30.4%)
Higher MMLU-Pro score (85.0% vs 48.3%)
Meta
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Meta
Llama 3.1 8B Instruct

FAQ

Common questions about DeepSeek-V3.2-Exp vs Llama 3.1 8B Instruct

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and Llama 3.1 8B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Llama 3.1 8B Instruct scores GSM-8K (CoT): 84.5%, ARC-C: 83.4%, API-Bank: 82.6%, IFEval: 80.4%, BFCL: 76.1%.
Llama 3.1 8B Instruct is 9.0x cheaper for input tokens. DeepSeek-V3.2-Exp costs $0.27/M input and $0.41/M output via novita. Llama 3.1 8B Instruct costs $0.03/M input and $0.03/M output via lambda.
DeepSeek-V3.2-Exp supports 164K tokens and Llama 3.1 8B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (164K vs 131K), input pricing ($0.27 vs $0.03/M), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Llama 3.1 8B Instruct is developed by Meta.