Model Comparison
DeepSeek-V4-Flash-0731 vs Llama 3.2 11B InstructWhich is better in 2026?
Comparing DeepSeek-V4-Flash-0731 and Llama 3.2 11B Instruct across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V4-Flash-0731 vs Llama 3.2 11B Instruct — which is better?
DeepSeek-V4-Flash-0731 (by DeepSeek) and Llama 3.2 11B 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.
On price, Llama 3.2 11B Instruct is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V4-Flash-0731 if…
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Llama 3.2 11B Instruct if…
- cost matters — it's about 2.3x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and Llama 3.2 11B Instructdon'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
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 1.8x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 3.6x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
In conclusion, DeepSeek-V4-Flash-0731 is more expensive than Llama 3.2 11B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 293.4B more parameters than Llama 3.2 11B Instruct, making it 2767.9% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Llama 3.2 11B Instruct's 128,000 tokens. Llama 3.2 11B Instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V4-Flash-0731 is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Llama 3.2 11B Instruct supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
Llama 3.2 11B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
Llama 3.2 11B Instruct
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while Llama 3.2 11B Instruct uses Llama 3.2 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.2 Community License
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Llama 3.2 11B Instruct was released on 2024-09-25.
DeepSeek-V4-Flash-0731 is 22 months newer than Llama 3.2 11B Instruct.
Jul 31, 2026
3 days ago
1.8yr newerSep 25, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
Llama 3.2 11B Instruct has a documented knowledge cutoff of 2023-12-31, while DeepSeek-V4-Flash-0731's cutoff date is not specified.
We can confirm Llama 3.2 11B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek-V4-Flash-0731's cutoff date.
—
Dec 2023
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Fireworks, Novita. Llama 3.2 11B Instruct is available from DeepInfra, Sambanova, Bedrock, Groq, Together, Fireworks.
DeepSeek-V4-Flash-0731
Llama 3.2 11B Instruct
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Llama 3.2 11B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Llama 3.2 11B Instruct.