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ModelCap

Laguna M.1

Official publisher releaseOpen weights7d #43 → #44

Poolside·#44 of 274 on the current board

Laguna M.1 is a language model from Poolside. It ranks #44 of 274 on ModelCap's current board, with an Index score of 69.7, modeled from the publisher's launch results against measured models. Its score range of 62.3–77.2 spans positions #28–#70. Its weights are openly downloadable.

Figures as of 24 Sept 2026, 05:04 UTC · download the public dataset · methodology

ModelCap Index · Current board
69.7#44
Modeled from the publisher's launch results against measured models · range 62.3–77.2
Market Gravity
13.3Decreased by 0.2
Secondary market signal

OpenRouter endpoint status could not be refreshed. This model is not treated as currently served until a successful observation arrives.

Input
Self-hosted
weights only · no listed API price
Output
Self-hosted
weights only · no listed API price
Context
tokens
Providers
0
endpoints

Providers

Uptime measured over the last 30 minutes

Current provider status is unavailable.

Reported evaluation leads (3)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.

Dataset / taskMetricValueRevisionProvenance
harborframework/terminal-bench-2.0
terminalbench_2
45.8
Unpinned
not published
Reported
Used in launch estimate
ScaleAI/SWE-bench_Pro
SWE_Bench_Pro
49.2
Unpinned
not published
Reported
Used in launch estimate
SWE-bench/SWE-bench_Verified
swe_bench_%_resolved
74.6
Unpinned
not published
Reported
Used in launch estimate

ModelCap Index · Current board

Methodology
69.7
Modeled from the publisher's launch results against measured models
Current board
#44 of 274
Score range
62.3–77.2
Rank range
#28–#70
Technical details
Public rank basis
Modeled · peer benchmarks (architecture)
Evidence label
Modeled · peer benchmarks · global-corpus-prior over 223 held-out anchors (6%); launch card against 4 resolved peers on 4 rows (94%); optimism haircut 0 from cross-lab-probe; shrunk 0.8 toward the measured corpus
Index support
23.9% · limited
Identity binding
Exact catalogue product · poolside/poolside/Laguna-M.1/bf16 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata poolside/Laguna-M.1@2bf8a4ab6d2e8e1e0d92a41318532a0fee1640d6 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
69.7
How this position was produced · fused launch placement

No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.

Fused estimate
69.7 ± 5.8
Independent share
0%
Shrink toward corpus
-0.8
Peer ceiling share
0%
Optimism haircut
None required · cross lab probe, 9 probes
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
global-corpus-prior over 223 held-out anchors
56.9 ± 23.36%
Launch card against resolved peers · not independent
launch card against 4 resolved peers on 4 rows
70.6 ± 6.094%
  • · Launch card row swe-bench-multilingual: claims below every resolved peer
  • · Launch card row swe-bench-pro: claims below every resolved peer
  • · Launch card row swe-bench-verified: inside the resolved peer range
  • · Launch card row terminal-bench-2-0: inside the resolved peer range
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
Evidence status
No admitted measured evidence
General preference
Coding
Agents & tools
Reasoning
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
Liquidity (providers × uptime)
Open reach (HF downloads)
65.7
Surface (context / tools / modalities)
0.0
Freshness
68.1
  • · HF 30d downloads 4444
  • · Catalogue surface
  • · First seen 2026-06-15

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Experimental capability estimate

Estimate policy
34.3
18.4–50.3 uncertainty interval
Excluded from rank
Confidence
73%
Training support
232 models · 133 lineages
Out-of-domain check
in domain
Feature coverage
71%
Lineage-held-out error
9.3 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
47.9
partial · 52% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
8.0
Evaluation provenance
0.0

Not yet published: the base model it derives from, a current serving provider, measured provider uptime, published provider pricing, declared context and output limits, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
13.3
OpenRouter weekly popularity
Not listed

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
0.0

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
0.0

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
65.7

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
68.1

Time since first public availability, on a six-month half-life.

Specification

Model ID
poolside/Laguna-M.1
Inputs
Text
Outputs
Text
Cached input tokens
Not offered
First seen on OpenRouter
15 Jun 2026

Capabilities

  • Not supported: Reasoning
  • Not supported: Tool use
  • Not supported: Structured output
  • Not supported: Response format
  • Not supported: Moderated

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
apache-2.0
Pinned revision
2bf8a4ab6d2e
Parameters
225.8B
Architecture
LagunaForCausalLM
Model type
laguna
Hugging Face downloads (30d)
4K
Downloads (all time)
17K
Likes
146
Repository updated
14 Jul 2026, 08:33 UTC

Alternatives to Laguna M.1, by the numbers

Ranked neighbours

Models within 3 places of #44 on the ModelCap Index.

Other ranked Poolside models

The same publisher's other current models with a public Index position.

Laguna M.1: common questions

How does Laguna M.1 rank among AI models?

Laguna M.1 holds ModelCap Index position #44 of 274 ranked language models as of 24 September 2026, with an Index score of 69.7 (interval 62.3–77.2); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Laguna M.1 cost per 1M tokens?

No live API price is listed for Laguna M.1 in the current snapshot as of 24 September 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.

Is Laguna M.1 open-weight?

Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is poolside/Laguna-M.1 on Hugging Face.

Which benchmarks has Laguna M.1 been evaluated on?

Laguna M.1's Index position rests on the evidence listed on this page; it has no result on the public boards ModelCap tracks as separate leaderboards as of 24 September 2026. The evidence panel names each source and its publication date.

When was Laguna M.1 released?

Laguna M.1 first appeared in the catalogue on 15 Jun 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.