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DeepSeek-V4.1-Flash-1017 vs Laguna S 2.1

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 39.7. Laguna S 2.1 is 4.2x cheaper per token.

DeepSeek · Poolside · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 39.7, ranking #15 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Laguna S 2.1 is roughly 4.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

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 51.2 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Laguna S 2.1

  • cost matters — it's about 4.2x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Laguna S 2.1
Poolside
Core performance indexes
LLM Stats Score
51.2
#15
39.7
#73
Reasoning
48.8
#18
39.7
#71
Coding
39.3
#14
29.1
#69
Agents
38.7
#8
23.3
#75
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.30 / M
$0.10 / M
Output price
$1.20 / M
$0.20 / M
Context window
1,048,576
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
Laguna S 2.1
Tool use
31.3#6
15.3#107
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 6 for Laguna S 2.1

1 shared

DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (DeepSWE 1.1), while Laguna S 2.1 is better at 0 benchmarks.

DeepSeek-V4.1-Flash-1017 significantly outperforms across most benchmarks.

Thu Oct 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Laguna S 2.1 costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 3.0x more expensive than Laguna S 2.1 ($0.10/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 6.0x more expensive than Laguna S 2.1 ($0.20/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than Laguna S 2.1.*

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

Lowest available price from all providers
Thu Oct 22 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Poolside
Laguna S 2.1
Input tokens$0.10
Output tokens$0.20
Best providerPoolside
Notice missing or incorrect data?

Model Size

Parameter count comparison

645.2B diff

DeepSeek-V4.1-Flash-1017 has 645.2B more parameters than Laguna S 2.1, making it 546.8% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Poolside
Laguna S 2.1
118.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
118.0B
Laguna S 2.1

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. Only DeepSeek-V4.1-Flash-1017 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Poolside
Laguna S 2.1
Input1,048,576 tokens
Output- tokens
Thu Oct 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Laguna S 2.1 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

Laguna S 2.1

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Laguna S 2.1 uses OpenMDW License v1.1.

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

DeepSeek-V4.1-Flash-1017

MIT

Open weights

Laguna S 2.1

OpenMDW License v1.1

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Laguna S 2.1 was released on 2026-07-21.

DeepSeek-V4.1-Flash-1017 is 3 months newer than Laguna S 2.1.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

5 days ago

2mo newer
Laguna S 2.1

Jul 21, 2026

3 months 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. Laguna S 2.1 is available from Poolside.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Laguna S 2.1

poolside logo
Poolside
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
* 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 Laguna S 2.1 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Laguna S 2.1
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Laguna S 2.1.

Which is better, DeepSeek-V4.1-Flash-1017 or Laguna S 2.1?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 39.7. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Laguna S 2.1 is made by Poolside. 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 Laguna S 2.1 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%. Laguna S 2.1 scores SWE-bench Multilingual: 78.5%, Terminal-Bench 2.1: 70.2%, SWE-Bench Pro: 59.4%, Toolathlon: 49.7%, SWE Atlas - Codebase QnA: 46.2%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Laguna S 2.1?

Laguna S 2.1 is 3.0x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Laguna S 2.1 costs $0.10/M input and $0.20/M output via poolside.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Laguna S 2.1?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Laguna S 2.1 supports 1.0M 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 Laguna S 2.1?

Key differences include LLM Stats Score (51.2 vs 39.7), input pricing ($0.30 vs $0.10/M), multimodal support (yes vs no), licensing (MIT vs OpenMDW License v1.1). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Laguna S 2.1?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Laguna S 2.1 is developed by Poolside.

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