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Laguna S 2.1 vs Pareto 26.9

Laguna S 2.1 costs 41.7x less per output token than Pareto 26.9 ($0.18 vs $7.50 per million). Updated October 22, 2026; no benchmark has tested both models yet.

P Laguna S 2.1Poolside
Coding
No data
Overall
No data
Output $/M
$0.18
U Pareto 26.9Unbiased
Coding
No data
Overall
No data
Output $/M
$7.50
vs $0.18 vs $7.50 per 1M output tokens. Laguna S 2.1 is 41.7x cheaper.

Laguna S 2.1 or Pareto 26.9: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Laguna S 2.1 for output tokens 41.7x cheaper ($0.18 vs $7.50 per million) and a larger context window (1.05M against 262K tokens).

No benchmark has tested either model yet, so price and context are the only way to compare them.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Laguna S 2.1 not benchmarked, Pareto 26.9 not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
Laguna S 2.1 $0.18 against Pareto 26.9 $7.50 per million output tokens, 41.7x apart.
Context window
Laguna S 2.1 takes 1.05M tokens, Pareto 26.9 262K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Laguna S 2.1$0.0002Fits in one request
Pareto 26.9$0.0063Fits in one request

Laguna S 2.1 costs less

Repository review

50K input + 3K output tokens

Laguna S 2.1$0.0050Fits in one request
Pareto 26.9$0.147Fits in one request

Laguna S 2.1 costs less

Agent loop

200K input + 10K output tokens

Laguna S 2.1$0.020Fits in one request
Pareto 26.9$0.575Fits in one request

Laguna S 2.1 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Laguna S 2.1 and Pareto 26.9
SpecificationPoolside Laguna S 2.1Pareto 26.9
MakerPoolsideUnbiased
WeightsOpen weightsNo public weights listed
ReleasedJuly 21, 2026October 13, 2026
Context window1.05M262K
Input $/Mtok$0.09$2.50
Output $/Mtok$0.18$7.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Laguna S 2.1 better than Pareto 26.9 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Laguna S 2.1 for output tokens 41.7x cheaper ($0.18 vs $7.50 per million) and a larger context window (1.05M against 262K tokens).

Which is cheaper, Laguna S 2.1 or Pareto 26.9?

Laguna S 2.1 costs $0.09 per million input tokens and $0.18 per million output tokens; Pareto 26.9 costs $2.50 and $7.50. Cost per solved task is known for neither of them.

Which has the bigger context window, Laguna S 2.1 or Pareto 26.9?

Laguna S 2.1, with 1.05M tokens against 262K.

Has any benchmark tested both Laguna S 2.1 and Pareto 26.9?

No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 22, 2026.

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