AI model comparison

DeepSeek V4 Pro vs Laguna S 2.1

Compare pricing, context limits, supported inputs and deployment options to choose a model for your workflow.

DeepSeek V4 Pro from DeepSeek lists 1M context, 384K maximum output, $0.435 input per 1M tokens, $0.87 output per 1M tokens. Laguna S 2.1 from Poolside lists 1.05M context, 32.77K maximum output, $0.10 input per 1M tokens, $0.20 output per 1M tokens. Compare the inputs, outputs and deployment options below to see which fits your workflow.

Side-by-sideCapabilities and practical differences

DeepSeek

DeepSeek V4 Pro

DeepSeek V4 Pro from DeepSeek: Open MoE flagship with million-token context for coding and long agent runs.

Context
1M
Max output
384K
Input / 1M tokens
$0.435
Output / 1M tokens
$0.87

Accepts

  • Text input

Produces

  • Text output
VS

Poolside

Laguna S 2.1

Laguna S 2.1 from Poolside: Agentic coding model from Poolside in the XS size class for local deployment.

Context
1.05M
Max output
32.77K
Input / 1M tokens
$0.10
Output / 1M tokens
$0.20

Accepts

  • Text input

Produces

  • Text output

At a glance

Key differences

Compare the available figures below, then try both models on the work you need to do.

DeepSeek V4 Pro

  • Maximum output: 384K

Laguna S 2.1

  • Context capacity: 1.05M
  • Input price: $0.10
  • Output price: $0.20

Context capacity

Higher listed limit

DeepSeek V4 Pro:1M

Laguna S 2.1:1.05M

Laguna S 2.1

Maximum output

Higher listed limit

DeepSeek V4 Pro:384K

Laguna S 2.1:32.77K

DeepSeek V4 Pro

Input price

Lower listed token rate

DeepSeek V4 Pro:$0.435

Laguna S 2.1:$0.10

Laguna S 2.1

Output price

Lower listed token rate

DeepSeek V4 Pro:$0.87

Laguna S 2.1:$0.20

Laguna S 2.1

Specifications

Pricing, limits and capabilities

Specifications for DeepSeek V4 Pro and Laguna S 2.1. Higher limits and lower prices describe these figures only.
SpecificationDeepSeek V4 ProLaguna S 2.1
ProviderDeepSeekPoolside
Listed pricing routeDeepSeekPoolside
Model familydeepseek-thinkinglaguna
Accepted inputstexttext
Produced outputstexttext
Context window1M1.05MHigher
Max output384KHigher32.77K
Input price / 1M$0.435$0.10Lower
Output price / 1M$0.87$0.20Lower
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputNot documentedNot documented
Audio inputNot documentedNot documented
Structured outputDocumentedNot documented
LicenseOpen weightsOpen weights

Workload guidance

Which model should you choose?

Consider DeepSeek V4 Pro if you need larger maximum output. Consider Laguna S 2.1 if you need larger context or a lower listed input rate or a lower listed output rate. Test both on the same representative examples and judge the output against your acceptance criteria. Include tool failures, retries and the time to a completed task.

Documentation and model profiles

Explore each model’s features, API requirements and licence terms in the sources below.

Questions people ask

It brings together documented inputs and outputs, token limits, deployment terms and available pricing. When both models have source-linked, verified results on a shared benchmark, those results are shown with their individual sources. The comparison is a starting point for evaluating your own workload.

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