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DeepSeek-V4.1-Flash vs Laguna S 2.1

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 40.9. Laguna S 2.1 is 2.6x cheaper per token.

DeepSeek · Poolside · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 40.9, ranking #13 overall.

In the 2 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, Laguna S 2.1 is roughly 2.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Laguna S 2.1 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

  • overall performance matters — it scores 51.8 and ranks #13 on LLM Stats
  • your work emphasizes coding and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Sep 2026

Choose Laguna S 2.1

  • cost matters — it's about 2.6x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Laguna S 2.1
Poolside
Core performance indexes
LLM Stats Score
51.8
#13
40.9
#53
Reasoning
48.9
#18
40.4
#53
Coding
44.2
#5
31.0
#45
Agents
41.1
#4
24.6
#50
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.22 / M
$0.10 / M
Output price
$0.66 / M
$0.20 / M
Context window
1,040,000
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
Laguna S 2.1
Tool use
34.8#2
17.4#73
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

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

2 shared

DeepSeek-V4.1-Flash outperforms in 2 benchmarks (DeepSWE 1.1, Terminal-Bench 2.1), while Laguna S 2.1 is better at 0 benchmarks.

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

Sun Sep 20 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 ($0.22/1M tokens) is 2.2x more expensive than Laguna S 2.1 ($0.10/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 3.3x more expensive than Laguna S 2.1 ($0.20/1M tokens).

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

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

Lowest available price from all providers
Sun Sep 20 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
Poolside
Laguna S 2.1
Input tokens$0.10
Output tokens$0.20
Best providerPoolside
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

645.2B diff

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

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

Context Window

Maximum input and output token capacity

Laguna S 2.1 accepts 1,048,576 input tokens compared to DeepSeek-V4.1-Flash's 1,040,000 tokens. Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Poolside
Laguna S 2.1
Input1,048,576 tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

Laguna S 2.1

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash 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

MIT

Open weights

Laguna S 2.1

OpenMDW License v1.1

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Laguna S 2.1 was released on 2026-07-21.

DeepSeek-V4.1-Flash is 2 months newer than Laguna S 2.1.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

1mo newer
Laguna S 2.1

Jul 21, 2026

2 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 is available from Fireworks, DeepInfra, DeepSeek, Novita. Laguna S 2.1 is available from Poolside.

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

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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and Laguna S 2.1 side-by-side, then vote on the output you prefer.

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

FAQ

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

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

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 40.9. DeepSeek-V4.1-Flash 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 compare to Laguna S 2.1 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%. 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 cheaper than Laguna S 2.1?

Laguna S 2.1 is 2.2x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. 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 and Laguna S 2.1?

DeepSeek-V4.1-Flash 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 and Laguna S 2.1?

Key differences include LLM Stats Score (51.8 vs 40.9), context window (1.0M vs 1.0M), input pricing ($0.22 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 and Laguna S 2.1?

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

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