Skip to content
ModelCap

HiLS Attention 7B

Official publisher releaseOpen weights7d #228 → #235

Tencent·#235 of 274 on the current board

HiLS Attention 7B is a language model from Tencent. It ranks #235 of 274 on ModelCap's current board, with an Index score of 14.1, carried over from the model it is built on. Its score range of 4.0–24.2 spans positions #206–#274. Its weights are openly downloadable.

Figures as of 24 Sept 2026, 05:59 UTC · download the public dataset · methodology

ModelCap Index · Current board
14.1#235
Carried over from the model it is built on · range 4.0–24.2
Market Gravity
9.8Decreased by 0.1
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
14.1
Carried over from the model it is built on
Current board
#235 of 274
Score range
4.0–24.2
Rank range
#206–#274
Technical details
Public rank basis
Modeled · lineage (lineage)
Evidence label
Modeled · lineage · finetune of allenai/Olmo-3-1025-7B · finetune (100%)
Index support
9.8% · weak
Identity binding
Exact catalogue product · tencent/tencent/HiLS-Attention-7B · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata tencent/HiLS-Attention-7B@837293e2aa5ae551439ebbd05783bddb92401853 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
14.1
Verified lineage
allenai/Olmo-3-1025-7B · minus 1.2 ( finetune)
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
14.1 ± 7.9
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
Verified lineage · not independent
finetune of allenai/Olmo-3-1025-7B · finetune
14.1 ± 7.9100%
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)
40.5
Surface (context / tools / modalities)
0.0
Freshness
74.6
  • · HF 30d downloads 529
  • · Catalogue surface
  • · First seen 2026-07-09

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
18.5
2.7–34.4 uncertainty interval
Excluded from rank
Confidence
74%
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
9.8
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%
40.5

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

Freshness5%
74.6

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

Specification

Model ID
tencent/HiLS-Attention-7B
Inputs
Text
Outputs
Text
Cached input tokens
Not offered
First seen on OpenRouter
9 Jul 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
837293e2aa5a
Parameters
7.3B
Architecture
HiLSForCausalLM
Model type
olmo_hils
Hugging Face downloads (30d)
529
Downloads (all time)
2K
Likes
24
Repository updated
27 Jul 2026, 08:55 UTC

Alternatives to HiLS Attention 7B, by the numbers

Ranked neighbours

Models within 3 places of #235 on the ModelCap Index.

Other ranked Tencent models

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

HiLS Attention 7B: common questions

How does HiLS Attention 7B rank among AI models?

HiLS Attention 7B holds ModelCap Index position #235 of 274 ranked language models as of 24 September 2026, with an Index score of 14.1 (interval 4.0–24.2); evidence: modeled · lineage. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does HiLS Attention 7B cost per 1M tokens?

No live API price is listed for HiLS Attention 7B 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 HiLS Attention 7B 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 tencent/HiLS-Attention-7B on Hugging Face.

Which benchmarks has HiLS Attention 7B been evaluated on?

HiLS Attention 7B'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 HiLS Attention 7B released?

HiLS Attention 7B first appeared in the catalogue on 9 Jul 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.