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DeepSeek-V4.1-Flash vs Llama 3.2 3B Instruct

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -6.1. Llama 3.2 3B Instruct is 26.4x cheaper per token.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to -6.1, ranking #12 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Llama 3.2 3B Instruct is roughly 26.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #12 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you process long inputs — it offers a 1,040,000 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose Llama 3.2 3B Instruct

  • cost matters — it's about 26.4x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Llama 3.2 3B Instruct
Meta
Core performance indexes
LLM Stats Score
51.8
#12
-6.1
#359
Reasoning
48.9
#17
-6.7
#353
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.22 / M
$0.01 / M
Output price
$0.66 / M
$0.02 / M
Context window
1,040,000
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash
Llama 3.2 3B Instruct
Math
35.2#43
-3.7#313
Tool use
35.1#2
4.7#155
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 15 for Llama 3.2 3B Instruct

1 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Llama 3.2 3B Instruct is better at 0 benchmarks.

DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.

Sat Sep 12 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Llama 3.2 3B Instruct costs less

For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 22.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 33.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).

In conclusion, DeepSeek-V4.1-Flash is more expensive than Llama 3.2 3B Instruct.*

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

Lowest available price from all providers
Sat Sep 12 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
Meta
Llama 3.2 3B Instruct
Input tokens$0.01
Output tokens$0.02
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

760.0B diff

DeepSeek-V4.1-Flash has 760.0B more parameters than Llama 3.2 3B Instruct, making it 23675.9% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Meta
Llama 3.2 3B Instruct
3.2Bparameters
763.2B
DeepSeek-V4.1-Flash
3.2B
Llama 3.2 3B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Llama 3.2 3B Instruct's 128,000 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Llama 3.2 3B Instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Meta
Llama 3.2 3B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Sep 12 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas Llama 3.2 3B Instruct does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Llama 3.2 3B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Llama 3.2 3B Instruct uses Llama 3.2 Community License.

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

DeepSeek-V4.1-Flash

MIT

Open weights

Llama 3.2 3B Instruct

Llama 3.2 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Llama 3.2 3B Instruct was released on 2024-09-25.

DeepSeek-V4.1-Flash is 24 months newer than Llama 3.2 3B Instruct.

DeepSeek-V4.1-Flash

Sep 10, 2026

2 days ago

2.0yr newer
Llama 3.2 3B Instruct

Sep 25, 2024

2.0 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-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. Llama 3.2 3B Instruct is available from DeepInfra.

DeepSeek-V4.1-Flash

fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Llama 3.2 3B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.01/1MOutput Price:Output: $0.02/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Llama 3.2 3B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Llama 3.2 3B Instruct.

Which is better, DeepSeek-V4.1-Flash or Llama 3.2 3B Instruct?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -6.1. DeepSeek-V4.1-Flash is made by DeepSeek and Llama 3.2 3B Instruct is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash compare to Llama 3.2 3B Instruct in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. Llama 3.2 3B Instruct scores NIH/Multi-needle: 84.7%, ARC-C: 78.6%, GSM8k: 77.7%, IFEval: 77.4%, HellaSwag: 69.8%.

Is DeepSeek-V4.1-Flash cheaper than Llama 3.2 3B Instruct?

Llama 3.2 3B Instruct is 22.0x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. Llama 3.2 3B Instruct costs $0.01/M input and $0.02/M output via deepinfra.

What are the context window sizes for DeepSeek-V4.1-Flash and Llama 3.2 3B Instruct?

DeepSeek-V4.1-Flash supports 1.0M tokens and Llama 3.2 3B 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-V4.1-Flash and Llama 3.2 3B Instruct?

Key differences include LLM Stats Score (51.8 vs -6.1), context window (1.0M vs 128K), input pricing ($0.22 vs $0.01/M), multimodal support (yes vs no), licensing (MIT vs Llama 3.2 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Llama 3.2 3B Instruct?

DeepSeek-V4.1-Flash is developed by DeepSeek and Llama 3.2 3B Instruct is developed by Meta.

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