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DeepSeek-V4.1-Flash-1017 vs Llama 3.2 3B Instruct

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -6.4. Llama 3.2 3B Instruct is 42.0x cheaper per token.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to -6.4, ranking #15 overall.

On price, Llama 3.2 3B Instruct is roughly 42.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017

  • overall performance matters — it scores 51.0 and ranks #15 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 Oct 2026

Choose Llama 3.2 3B Instruct

  • cost matters — it's about 42.0x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Llama 3.2 3B Instruct
Meta
Core performance indexes
LLM Stats Score
51.0
#15
-6.4
#384
Reasoning
48.6
#18
-7.0
#378
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.01 / M
Output price
$1.20 / M
$0.02 / M
Context window
1,048,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash-1017
Llama 3.2 3B Instruct
Math
31.8#67
-3.7#325
Tool use
30.9#7
4.7#175
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 15 for Llama 3.2 3B Instruct

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Llama 3.2 3B 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

Llama 3.2 3B Instruct costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 30.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 60.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 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
Mon Oct 19 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Meta
Llama 3.2 3B Instruct
Input tokens$0.01
Output tokens$0.02
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

760.0B diff

DeepSeek-V4.1-Flash-1017 has 760.0B more parameters than Llama 3.2 3B Instruct, making it 23675.9% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Meta
Llama 3.2 3B Instruct
3.2Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
3.2B
Llama 3.2 3B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Llama 3.2 3B Instruct's 128,000 tokens. DeepSeek-V4.1-Flash-1017 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-1017
Input1,048,576 tokens
Output393,216 tokens
Meta
Llama 3.2 3B Instruct
Input128,000 tokens
Output128,000 tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Llama 3.2 3B Instruct does not.

DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Llama 3.2 3B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 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-1017

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-1017 was released on 2026-10-17, while Llama 3.2 3B Instruct was released on 2024-09-25.

DeepSeek-V4.1-Flash-1017 is 25 months newer than Llama 3.2 3B Instruct.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

0 days ago

2.1yr newer
Llama 3.2 3B Instruct

Sep 25, 2024

2.1 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-1017 is available from DeepSeek. Llama 3.2 3B Instruct is available from DeepInfra.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
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?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Llama 3.2 3B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Llama 3.2 3B Instruct.

Which is better, DeepSeek-V4.1-Flash-1017 or Llama 3.2 3B Instruct?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -6.4. DeepSeek-V4.1-Flash-1017 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-1017 compare to Llama 3.2 3B Instruct in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. 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-1017 cheaper than Llama 3.2 3B Instruct?

Llama 3.2 3B Instruct is 30.0x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. 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-1017 and Llama 3.2 3B Instruct?

DeepSeek-V4.1-Flash-1017 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-1017 and Llama 3.2 3B Instruct?

Key differences include LLM Stats Score (51.0 vs -6.4), context window (1.0M vs 128K), input pricing ($0.30 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-1017 and Llama 3.2 3B Instruct?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Llama 3.2 3B Instruct is developed by Meta.

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