Data as of October 19, 2026 · How the score is built
Released Jul 21, 20261M context
Laguna S 2.1
Decision readingLaguna 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.
Released Jul 21, 2026 — see all recent releases
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 50Not eligible for a public rank
Price
$0.10input / $0.20 output
input median $0.75cached $0.010 · blended $0.15
Speed
Not measured
field median 94 tok/sTime to first token not measured
Context
1Mtokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Published rows are visible, but no category has enough eligible evidence for a comparative rank.
Validate before choosing
6 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
Source-linked · 6 displayable benchmark rows
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 | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| CodingRank Not rankedWeight 20%4 benchmarksVerified | 51.2 | 4 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
6 of 686 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow 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.
- Agentic2/2 verified
- Coding4/4 verified
- ReasoningNot measured
- MultimodalNot measured
- KnowledgeNot measured
- MultilingualNot measured
- Inst. FollowingNot measured
- MathNot 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
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score59.4% | Versus best verified row Best verified: Claude Opus 5.5 · 89.9% | Gap30.5 behind | Weight26% ref. weight | Provider exact |
| DeepSWE | Score40.4% | Versus best verified row Best verified: Muse Wonder Full · 79.0% | Gap38.6 behind | Weight15% ref. weight | Provider exact |
| SWE Multilingual | Score78.5% | Versus best verified row Best verified: Claude Opus 5.5 · 93.9% | Gap15.4 behind | Weight5% ref. weight | Provider exact |
| Terminal-Bench 2.1 | Score70.2% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap22.6 behind | WeightScored in Agentic | Provider exact |
Agentic2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.1 | Score70.2% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap22.6 behind | Weight8% ref. weight | Provider exact |
| Toolathlon-Verified | Score49.7% | Versus best verified row Best verified: Claude Opus 5 · 80.6% | Gap30.9 behind | Weight3% ref. weight | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 6 rowsLineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
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
- Laguna S 2.1 needs ~80GB VRAM (1× NVIDIA H100 (80GB)).
- Rate limits
- Not tracked yet
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, 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, Laguna XS 2.1. Its explicit predecessor is Laguna M.1. 6 of 686 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Last updated October 19, 2026. Runtime fields remain blank until a sourced snapshot exists.
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.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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 has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Laguna S 2.1 good for agentic tool use and computer tasks?
Laguna S 2.1 has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
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, Laguna XS 2.1. 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 686 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.