Skip to content
ModelCap

slm rag grpo merged

Official publisher releaseOpen weights

Canopus77

slm rag grpo merged is a language model from Canopus77. It does not hold a position on ModelCap's current board. Its weights are openly downloadable.

Figures as of 23 Sept 2026, 20:40 UTC · download the public dataset · methodology

ModelCap Index · Current board
57.2
Modeled from public metadata, not measured · range 27.4–87.0
Market Gravity
11.6Decreased by 1.2
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.

ModelCap Index · Current board

Methodology
57.2
Modeled from public metadata, not measured
Score range
27.4–87.0
Technical details
Public rank basis
Modeled · prior (architecture)
Evidence label
Modeled · prior · global-corpus-prior over 223 held-out anchors (100%)
Index support
4.5% · weak
Identity binding
Exact catalogue product · canopus77/canopus77/slm-rag-grpo-merged · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata canopus77/slm-rag-grpo-merged@154cc0c20060dbf0836e78c6c42fa1b8156c6b1f (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
57.2
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
57.2 ± 23.3
Independent share
0%
Shrink toward corpus
0.0
Optimism haircut
None applied
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
57.2 ± 23.3100%
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)
45.3
Surface (context / tools / modalities)
0.0
Freshness
95.7
  • · HF 30d downloads 531
  • · Catalogue surface
  • · First seen 2026-09-12

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
15.6
0.0–31.6 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
52.4
partial · 56% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
8.0
Evaluation provenance
0.0

Not yet published: 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
11.6
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%
45.3

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

Freshness5%
95.7

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

Specification

Model ID
canopus77/slm-rag-grpo-merged
Inputs
Text
Outputs
Text
Cached input tokens
Not offered
First seen on OpenRouter
12 Sept 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
154cc0c20060
Parameters
3.2B
Architecture
LlamaForCausalLM
Model type
llama
Hugging Face downloads (30d)
531
Downloads (all time)
531
Likes
0
Repository updated
12 Sept 2026, 08:12 UTC