DeepSeek-V4-Flash-0731 vs Llama 3.2 11B Instruct
DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to -1.3. Llama 3.2 11B Instruct is 1.8x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.7 to -1.3, ranking #35 overall.
On price, Llama 3.2 11B Instruct is roughly 1.8x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- overall performance matters — it scores 44.7 and ranks #35 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- 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
- cost matters — it's about 1.8x cheaper per token
At a glance
The differences that matter most.
Individual benchmarks
9 reported for DeepSeek-V4-Flash-0731 · 11 for Llama 3.2 11B Instruct
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.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.06/1M tokens) is 1.2x 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. DeepSeek-V4-Flash-0731 can generate longer responses up to 1,048,576 tokens, while Llama 3.2 11B Instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
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
1 months ago
1.8yr newerSep 25, 2024
2.0 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, Novita, Fireworks. 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
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.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Llama 3.2 11B Instruct.