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Laguna S 2.1

CurrentReleased Jul 21, 2026Open WeightReasoning1M context

Released Jul 21, 2026 see all recent releases

Decision reading
Laguna S 2.1 is tracked, but not publicly ranked yet. The profile exposes 6 sourced benchmark rows and leaves unsupported fields blank until a published record exists.

Data as of September 4, 2026 · How the score is built

Strongest published evidence

Agentic ranks #77. Particularly useful for coding agents, browser research, and computer-use workflows.

Validate before choosing

6 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

Unranked

field median 58.1

Not eligible for a public rank

Price

$0.10input / $0.20 output

input median $1

cached $0.010 · blended $0.15

Speed

Not measured

field median 92 tok/s

Time to first token not measured

Context

1Mtokens

field median 256,000

Reported for this model; direct source link not stored

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic2/2 verified
  2. Coding4/4 verified
  3. ReasoningNot measured
  4. KnowledgeNot measured
  5. MathNot measured
  6. MultilingualNot measured
  7. MultimodalNot measured
  8. Inst. FollowingNot measured
Verified sourceProvisionalNot measured

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Not published
Context window
1M
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Open weights under OpenMDW-1.1 are available on Hugging Face. Poolside also lists hosted access through OpenRouter, Baseten, Kilo, and its pool coding agent.
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.010 per million cached input tokens
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #77 of 151Percentile 49thWeight 22%2 benchmarksVerified48.2
CodingRank #87 of 183Percentile 53rdWeight 20%4 benchmarksVerified47.8
ReasoningWeight 17%0 benchmarksNot measuredNot measured
KnowledgeWeight 12%0 benchmarksNot measuredNot measured
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalWeight 12%0 benchmarksNot measuredNot measured
Inst. FollowingWeight 5%0 benchmarksNot measuredNot measured

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding4 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore59.4%Versus best verified row

Best verified: Claude Fable 5.1 · 81.2%

Gap21.8 behindWeightWeighted 25%
SWE MultilingualScore78.5%Versus best verified row

Best verified: Claude Opus 5 · 89.5%

Gap11 behindWeightWeighted 5%
Terminal-Bench 2.0Score70.2%Versus best verified row

Best verified: GPT-5.6 Sol · 91.9%

Gap21.7 behindWeightDisplay only
deepSweScore40.4%Versus best verified row

Best verified: Muse Spark 1.3 · 75.4%

Gap35 behindWeightDisplay only
Agentic2 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.0Score70.2%Versus best verified row

Best verified: GPT-5.6 Sol · 91.9%

Gap21.7 behindWeightWeighted 30%
Toolathlon-VerifiedScore49.7%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap30.9 behindWeightDisplay only

Lineage

The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Apr 28, 2026

    Laguna M.1

    Score 4.5 · Price not listed

  2. Jul 21, 2026 · you are here

    Laguna S 2.1

    Not publicly ranked · $0.1 / $0.2

s-2-1 · 118B-A8B

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

We track Laguna S 2.1, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.

Laguna S 2.1 is a open weight model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Open weights under OpenMDW-1.1 are available on Hugging Face. Poolside also lists hosted access through OpenRouter, Baseten, Kilo, and its pool coding agent.

Official exact-value snapshot from Poolside's July 21, 2026 launch post and matching Hugging Face model card. We map Terminal-Bench 2.1 to the existing Terminal-Bench key, plus SWE-bench Multilingual, SWE-bench Pro, DeepSWE v1.1, and Toolathlon Verified. Poolside also reports 46.2% on SWE Atlas (Codebase QnA), which remains outside the model-row schema. Poolside reports max-thinking results from its pool harness; benchmark-specific attempt counts and setup differences make these provider-reported rather than benchmark-native values.

Laguna S 2.1 sits in the Laguna family with Laguna M.1, Laguna XS.2. Its explicit predecessor is Laguna M.1. 6 of 422 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Agentic at #77, while its lowest eligible position is Coding at #87. particularly useful for coding agents, browser research, and computer-use workflows.

Radar

Laguna S 2.1 release history

Full release history

Radar confirmed these at the source. Already tracking Laguna S 2.1? See the free Radar Brief for what changes next.

Frequently asked questions

How does Laguna S 2.1 perform overall in AI benchmarks?

Laguna S 2.1 has 6 source-displayable benchmark rows, but it does not qualify for a public overall rank. The available rows remain visible by category without being converted into a site-wide score. Missing evidence stays blank instead of being estimated from an earlier model.

Is Laguna S 2.1 good for coding and programming?

Laguna S 2.1 ranks #87 out of 183 eligible models for coding and programming, with a public category score of 47.8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Laguna S 2.1 good for agentic tool use and computer tasks?

Laguna S 2.1 ranks #77 out of 151 eligible models for agentic tool use and computer tasks, with a public category score of 48.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Laguna S 2.1 open source?

Laguna S 2.1 is an open-weight model from Poolside. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Which sibling models are related to Laguna S 2.1?

Laguna S 2.1 belongs to the Laguna family. Related tracked variants include Laguna M.1, Laguna XS.2. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.

Does Laguna S 2.1 have full benchmark coverage on BenchLM?

No. Laguna S 2.1 currently has 6 source-displayable rows across 422 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Laguna S 2.1?

Laguna S 2.1 has a reported context window of 1M in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.

Compare Laguna S 2.1 with every tracked model410 comparisons

Last updated September 4, 2026. Runtime fields remain blank until a sourced snapshot exists.

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