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Model comparison

DeepSeek V4 Pro vs Laguna S 2.1

Data verified

Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

60.66/100
No comparison
Poolside
N/A
1 category wins1 category wins

Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); Laguna S 2.1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V4 Pro and Laguna S 2.1 share 4 comparable benchmark results. 2 of 8 categories are comparable. 19 results are unique to DeepSeek V4 Pro; 2 to Laguna S 2.1.

Updated July 21, 2026
Shared results
4
DeepSeek V4 Pro only
19
Laguna S 2.1 only
2
Comparable categories
2 / 8

Treat this as a split decision. DeepSeek V4 Pro makes more sense if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model; Laguna S 2.1 is the better fit if agentic is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

DeepSeek V4 Pro and Laguna S 2.1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

DeepSeek V4 Pro is also the more expensive model on tokens at $0.43 input / $0.87 output per 1M tokens, versus $0.10 input / $0.20 output per 1M tokens for Laguna S 2.1. That is roughly 4.3x on output cost alone. Laguna S 2.1 is the reasoning model in the pair, while DeepSeek V4 Pro is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for DeepSeek V4 Pro and Laguna S 2.1
CategoryDeepSeek V4 ProΔLaguna S 2.1
AgenticDeepSeek V4 Pro59.1Margin 11.1Laguna S 2.170.2
CodingDeepSeek V4 Pro65.3Margin 5.9Laguna S 2.159.4
KnowledgeDeepSeek V4 Pro41.3MarginNo overlapLaguna S 2.1Not measured
MathDeepSeek V4 Pro31.7MarginNo overlapLaguna S 2.1Not measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · DeepSeek V4 ProB · Laguna S 2.1
  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 59.1%B 70.2%
    Winner: Laguna S 2.1Δ 11.1
    Terminal-Bench 2.0: DeepSeek V4 Pro scored 59.1%; Laguna S 2.1 scored 70.2%. Laguna S 2.1 wins this benchmark.
  2. SWE-bench Pro

    Coding
    Source ↗
    A 52.1%B 59.4%
    Winner: Laguna S 2.1Δ 7.3
    SWE-bench Pro: DeepSeek V4 Pro scored 52.1%; Laguna S 2.1 scored 59.4%. Laguna S 2.1 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricDeepSeek V4 ProLaguna S 2.1Comparison
Input / output priceUSD per 1M tokensDeepSeek V4 Pro$0.435 input / $0.87 outputLaguna S 2.1$0.1 input / $0.2 outputLaguna S 2.1 has the lower combined listed price.
Generation speedtokens per secondDeepSeek V4 ProNot availableLaguna S 2.1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V4 ProNot availableLaguna S 2.1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V4 Pro1MLaguna S 2.11MListed context windows are equal.

Benchmark Deep Dive

AgenticLaguna S 2.1 wins
BenchmarkDeepSeek V4 ProLaguna S 2.1Result
Terminal-Bench 2.0Source 59.1%70.2%Laguna S 2.1 leads
MCP AtlasSource 69.4%Not comparable
ToolathlonSource 46.3%Not comparable
Claw-EvalSource 59.8%Not comparable
Gert LabsSource 50.28%Not comparable
ResearchClawBenchSource 17.1%Not comparable
Toolathlon-VerifiedSource 49.7%Not comparable
CodingDeepSeek V4 Pro wins
BenchmarkDeepSeek V4 ProLaguna S 2.1Result
SWE-bench VerifiedSource 73.6%Not comparable
SWE-bench ProSource 52.1%59.4%Laguna S 2.1 leads
SWE MultilingualSource 69.8%78.5%Laguna S 2.1 leads
Terminal-Bench 2.0Source 59.1%70.2%Laguna S 2.1 leads
deepSweSource 40.4%Not comparable
Reasoning
BenchmarkDeepSeek V4 ProLaguna S 2.1Result
MRCR 1MSource 44.7%Not comparable
CorpusQA 1MSource 35.6%Not comparable
Knowledge
BenchmarkDeepSeek V4 ProLaguna S 2.1Result
MMLU-ProSource 82.9%Not comparable
SimpleQASource 45%Not comparable
Chinese-SimpleQASource 75.8%Not comparable
GPQASource 72.9%Not comparable
GPQA-DSource 72.9%Not comparable
HLESource 7.7%Not comparable
Math
BenchmarkDeepSeek V4 ProLaguna S 2.1Result
HMMT Feb 2026Source 31.7%Not comparable
IMOAnswerBenchSource 35.3%Not comparable
ApexSource 0.4%Not comparable
Apex ShortlistSource 9.2%Not comparable
Multimodal
BenchmarkDeepSeek V4 ProLaguna S 2.1Result
Design Arena WebsiteSource 1264Not comparable
Frequently Asked Questions (3)

Which is better, DeepSeek V4 Pro or Laguna S 2.1?

DeepSeek V4 Pro and Laguna S 2.1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for coding, DeepSeek V4 Pro or Laguna S 2.1?

DeepSeek V4 Pro has the edge for coding in this comparison, averaging 65.3 versus 59.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, DeepSeek V4 Pro or Laguna S 2.1?

Laguna S 2.1 has the edge for agentic tasks in this comparison, averaging 70.2 versus 59.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Related Comparisons

Last updated: July 21, 2026

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