Model A

Poolside

1.53/100

Estimated · Public rank #251

90% interval 0.0–11.4

Laguna XS.2 vs Qwen3.6 Plus

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Qwen3.6 Plus

Alibaba

60.4/100

Supported · Public rank #64

90% interval 50.8–70.0

Decision reading

Qwen3.6 Plus has the higher public score, 60.4 versus 1.53, and the 90% score intervals do not overlap.

9 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Coding work
Code generation, repair, and software-engineering tasks
Qwen3.6 Plus
Qwen3.6 Plus leads on the public coding lane, 46.9 to 24.7, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
Qwen3.6 Plus
Qwen3.6 Plus has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Laguna XS.2 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

1 Laguna XS.2 only

9 Shared

39 Qwen3.6 Plus only

Shared results: 9
Laguna XS.2 only: 1
Qwen3.6 Plus only: 39
Like-for-like categories: 1 / 8

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Coding

Like-for-like

Laguna XS.2: 24.7; Supported · #148/151
Qwen3.6 Plus: 46.9; Supported · #76/151
Basis: BenchAlign lane · 6 vs 7 public rows
Reading: Qwen3.6 Plus leads

Agentic

Directional only

Laguna XS.2: 22.4; Estimated · #149/152
Qwen3.6 Plus: 36.0; Supported · #132/152
Basis: BenchAlign lane · 2 vs 13 public rows
Reading: Directional only

Knowledge

Directional only

Laguna XS.2: 17.7; Estimated · #183/183
Qwen3.6 Plus: 54.0; Supported · #60/183
Basis: BenchAlign lane · 2 vs 8 public rows
Reading: Directional only

Reasoning

Not comparable

Laguna XS.2: Not ranked
Qwen3.6 Plus: 60.1; Unranked · 4 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Laguna XS.2: Not ranked
Qwen3.6 Plus: 62.4; #4/7
Basis: Provisional lane · 0 vs 4 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Laguna XS.2: Not ranked
Qwen3.6 Plus: 69.7; #4/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Laguna XS.2: Not ranked
Qwen3.6 Plus: 66.3; #22/48
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Laguna XS.2: Not ranked
Qwen3.6 Plus: 85.5; #43/123
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Laguna XS.2 and Qwen3.6 Plus
Category	Laguna XS.2	Qwen3.6 Plus	Basis	Reading
Coding	24.7Supported · #148/151	46.9Supported · #76/151	Like-for-likeBenchAlign lane · 6 vs 7 public rows	Qwen3.6 Plus leads
Agentic	22.4Estimated · #149/152	36.0Supported · #132/152	Directional onlyBenchAlign lane · 2 vs 13 public rows	Directional only
Knowledge	17.7Estimated · #183/183	54.0Supported · #60/183	Directional onlyBenchAlign lane · 2 vs 8 public rows	Directional only
Reasoning	Not ranked	60.1Unranked · 4 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	62.4#4/7	Not comparableProvisional lane · 0 vs 4 weighted rows	Not comparable
Multilingual	Not ranked	69.7#4/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	Not ranked	66.3#22/48	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Instruction following	Not ranked	85.5#43/123	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Terminal-Bench 2.0
Agentic
Laguna XS.2: 35.7%Qwen3.6 Plus: 61.6%Normalized gap 25.9Laguna XS.2 source Qwen3.6 Plus source
MMLU-Pro (Vals)
Knowledge
Laguna XS.2: 69.1%Qwen3.6 Plus: 87.7%Normalized gap 18.6Laguna XS.2 source Qwen3.6 Plus source
LiveCodeBench (Vals)
Coding
Laguna XS.2: 67.8%Qwen3.6 Plus: 86.0%Normalized gap 18.2Laguna XS.2 source Qwen3.6 Plus source
SWE Multilingual
Coding
Laguna XS.2: 57.7%Qwen3.6 Plus: 73.8%Normalized gap 16.1Laguna XS.2 source Qwen3.6 Plus source
SWE-bench Pro
Coding
Laguna XS.2: 46.3%Qwen3.6 Plus: 56.6%Normalized gap 10.3Laguna XS.2 source Qwen3.6 Plus source

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Laguna XS.2: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.6 Plus: API rate not published; Fits in one request

Laguna XS.2 has no comparable published API token rate. Qwen3.6 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Laguna XS.2: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.6 Plus: API rate not published; Fits in one request

Laguna XS.2 has no comparable published API token rate. Qwen3.6 Plus has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Laguna XS.2: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable
Qwen3.6 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

Laguna XS.2 has no comparable published API token rate. Qwen3.6 Plus has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationLaguna XS.2Qwen3.6 Plus

Context window

Maximum documented context; output-token limits may be lower.

Laguna XS.2

256K

Qwen3.6 Plus

API model ID

Laguna XS.2

Not sourced

Qwen3.6 Plus

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Laguna XS.2

No comparable hosted API rate

Qwen3.6 Plus

No comparable hosted API rate

Documented inputs

Laguna XS.2

Not sourced

Qwen3.6 Plus

Not sourced

Documented outputs

Laguna XS.2

Not sourced

Qwen3.6 Plus

Not sourced

Provider availability

Laguna XS.2

Not sourced

Qwen3.6 Plus

Not sourced

Reasoning profile

Laguna XS.2

Reasoning

Qwen3.6 Plus

Reasoning

Weight access

Laguna XS.2

Open Weight

Qwen3.6 Plus

Proprietary

License

Laguna XS.2

Open Weight

Qwen3.6 Plus

Proprietary

Release date

Laguna XS.2

2026-04-28

Qwen3.6 Plus

2026-04-02

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: Qwen3.6 Plus has the higher public score, 60.4 versus 1.53, and the 90% score intervals do not overlap.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Qwen3.6 Plus has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence49 rows

Agentic

Terminal-Bench 2.0
Laguna XS.235.7%
Source
Qwen3.6 Plus61.6%
Source
Qwen3.6 Plus leads this result
Terminal-Bench 2.1 (Vals)
Laguna XS.225.8%
Source
Qwen3.6 Plus53.2%
Source
Qwen3.6 Plus leads this result
Claw-Eval
Laguna XS.2—
Qwen3.6 Plus58.8%
Source
Not directly comparable
QwenClawBench
Laguna XS.2—
Qwen3.6 Plus57.2%
Source
Not directly comparable
τ³-bench results
Laguna XS.2—
Qwen3.6 Plus70.7%
Source
Not directly comparable
VITA-Bench
Laguna XS.2—
Qwen3.6 Plus44.3%
Source
Not directly comparable
DeepPlanning
Laguna XS.2—
Qwen3.6 Plus41.5%
Source
Not directly comparable
Toolathlon
Laguna XS.2—
Qwen3.6 Plus39.8%
Source
Not directly comparable
MCP Atlas
Laguna XS.2—
Qwen3.6 Plus48.2%
Source
Not directly comparable
MCP-Tasks
Laguna XS.2—
Qwen3.6 Plus74.1%
Source
Not directly comparable
WideResearch
Laguna XS.2—
Qwen3.6 Plus74.3%
Source
Not directly comparable
Gert Labs
Laguna XS.2—
Qwen3.6 Plus50.60%
Source
Not directly comparable
ResearchClawBench
Laguna XS.2—
Qwen3.6 Plus18.0%
Source
Not directly comparable

Coding

SWE-bench Verified
Laguna XS.269.9%
Source
Qwen3.6 Plus78.8%
Source
Qwen3.6 Plus leads this result
SWE Multilingual
Laguna XS.257.7%
Source
Qwen3.6 Plus73.8%
Source
Qwen3.6 Plus leads this result
SWE-bench Pro
Laguna XS.246.3%
Source
Qwen3.6 Plus56.6%
Source
Qwen3.6 Plus leads this result
Terminal-Bench 2.0
Laguna XS.235.7%
Source
Qwen3.6 Plus—
Not directly comparable
LiveCodeBench (Vals)
Laguna XS.267.8%
Source
Qwen3.6 Plus86.0%
Source
Qwen3.6 Plus leads this result
SWE-bench (Vals)
Laguna XS.255.2%
Source
Qwen3.6 Plus73.4%
Source
Qwen3.6 Plus leads this result
LiveCodeBench v6
Laguna XS.2—
Qwen3.6 Plus87.1%
Source
Not directly comparable
Vibe Code Bench
Laguna XS.2—
Qwen3.6 Plus25.56%
Source
Not directly comparable

Reasoning

AI-Needle
Laguna XS.2—
Qwen3.6 Plus68.3%
Source
Not directly comparable
LongBench v2
Laguna XS.2—
Qwen3.6 Plus62%
Source
Not directly comparable

Knowledge

GPQA Diamond (Vals)
Laguna XS.255.1%
Source
Qwen3.6 Plus87.4%
Source
Qwen3.6 Plus leads this result
MMLU-Pro (Vals)
Laguna XS.269.1%
Source
Qwen3.6 Plus87.7%
Source
Qwen3.6 Plus leads this result
GPQA
Laguna XS.2—
Qwen3.6 Plus90.4%
Source
Not directly comparable
SuperGPQA
Laguna XS.2—
Qwen3.6 Plus71.6%
Source
Not directly comparable
MMLU-Pro
Laguna XS.2—
Qwen3.6 Plus88.5%
Source
Not directly comparable
MMLU-Redux
Laguna XS.2—
Qwen3.6 Plus94.5%
Source
Not directly comparable
C-Eval
Laguna XS.2—
Qwen3.6 Plus93.3%
Source
Not directly comparable
HLE
Laguna XS.2—
Qwen3.6 Plus28.8%
Source
Not directly comparable

Math

AIME26
Laguna XS.2—
Qwen3.6 Plus95.3%
Source
Not directly comparable
HMMT Feb 2025
Laguna XS.2—
Qwen3.6 Plus96.7%
Source
Not directly comparable
HMMT Nov 2025
Laguna XS.2—
Qwen3.6 Plus94.6%
Source
Not directly comparable
HMMT Feb 2026
Laguna XS.2—
Qwen3.6 Plus87.8%
Source
Not directly comparable
MMAnswerBench
Laguna XS.2—
Qwen3.6 Plus83.8%
Source
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Laguna XS.2—
Qwen3.6 Plus26.207%
Source
Not directly comparable
FrontierMath v2 (Tier 4)
Laguna XS.2—
Qwen3.6 Plus8.333%
Source
Not directly comparable

Multilingual

MMLU-ProX
Laguna XS.2—
Qwen3.6 Plus84.7%
Source
Not directly comparable
NOVA-63
Laguna XS.2—
Qwen3.6 Plus57.9%
Source
Not directly comparable

Multimodal

MMMU
Laguna XS.2—
Qwen3.6 Plus86.0%
Source
Not directly comparable
MMMU-Pro
Laguna XS.2—
Qwen3.6 Plus78.8%
Source
Not directly comparable
MathVision
Laguna XS.2—
Qwen3.6 Plus88.0%
Source
Not directly comparable
VideoMMMU
Laguna XS.2—
Qwen3.6 Plus84.0%
Source
Not directly comparable
ScreenSpot Pro
Laguna XS.2—
Qwen3.6 Plus68.2%
Source
Not directly comparable
CharXiv
Laguna XS.2—
Qwen3.6 Plus81.5%
Source
Not directly comparable
V*
Laguna XS.2—
Qwen3.6 Plus96.9%
Source
Not directly comparable

Instruction following

IFEval
Laguna XS.2—
Qwen3.6 Plus94.3%
Source
Not directly comparable
IFBench
Laguna XS.2—
Qwen3.6 Plus75.8%
Source
Not directly comparable

Frequently asked questions

Which is better, Laguna XS.2 or Qwen3.6 Plus?

Qwen3.6 Plus has the higher public score, 60.4 versus 1.53, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Laguna XS.2 or Qwen3.6 Plus?

Qwen3.6 Plus leads the public coding lane, 46.9 to 24.7, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Laguna XS.2 or Qwen3.6 Plus?

Qwen3.6 Plus scores higher for agentic tasks on the public lane, 36 to 22.4. Laguna XS.2 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Laguna XS.2 or Qwen3.6 Plus?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Laguna XS.2 or Qwen3.6 Plus?

Qwen3.6 Plus has the larger documented context window: 1M, compared with 256K.

Related comparisons

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Last updated September 10, 2026

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Laguna XS.2 vs Qwen3.6 Plus

Which one for your work

Coding work

Long documents

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Coding

Agentic

Knowledge

Reasoning

Math

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, Laguna XS.2 or Qwen3.6 Plus?

Which is better for coding, Laguna XS.2 or Qwen3.6 Plus?

Which is better for agentic tasks, Laguna XS.2 or Qwen3.6 Plus?

Which costs less, Laguna XS.2 or Qwen3.6 Plus?

Which has the larger context window, Laguna XS.2 or Qwen3.6 Plus?

Related comparisons

Watch Laguna XS.2 vs Qwen3.6 Plus