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ModelCap

KAT Coder V2.5 Dev

Current board #38Official publisher releaseOpen weights

Kwaipilot·Kwaipilot/KAT-Coder-V2.5-Dev

KAT Coder V2.5 Dev is ModelCap current-board rank #38 with Index 67.8 (Modeled · peer benchmarks), from the ModelCap Index as of 22 Sept 2026, 03:10 UTC.

KAT Coder V2.5 Dev weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 03:10 UTC.

Snapshot facts · download the public dataset · methodology

ModelCap Index · Current board
67.8#38
Estimated · 26% support · score interval 54.2–81.4
No admitted evaluation publication timestamp yet
Market Gravity
15.4Decreased 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
Gateway spend
latest · Vercel share

Providers

Uptime measured over the last 30 minutes

Current provider status is unavailable.

ModelCap Index · Current board

Methodology
67.8
Modeled · peer benchmarks · calibrated architecture-and-release-era fallback from static public metadata
Current board
#38
Public rank basis
Modeled · peer benchmarks (architecture)
Index support
26.0% · limited
Index interval
54.2–81.4
Rank posterior
Not available
Top 5 / Top 10 probability
Not available / Not available
Posterior as of
Snapshot timestamp unavailable
Evidence as of
No admitted evaluation publication timestamp
Identity binding
Exact catalogue product · kwaipilot/Kwaipilot/KAT-Coder-V2.5-Dev · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata Kwaipilot/KAT-Coder-V2.5-Dev@7be56fe773e72b6f5ca93c1ae45d828ddb893922 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
67.8
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
67.8 ± 10.6
Independent share
0%
Shrink toward corpus
-3.6
Peer ceiling share
100%
Optimism haircut
None required · cross lab probe, 1 probe
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
global-corpus-prior over 203 held-out anchors
54.9 ± 22.722%
Launch card against resolved peers · not independent
launch card against 2 resolved peers on 4 rows
71.4 ± 12.078%
  • · Launch card row scicode: claims above every resolved peer
  • · Launch card row swe-bench-multilingual: claims above every resolved peer
  • · Launch card row swe-bench-pro: claims above every resolved peer
  • · Launch card row swe-bench-verified: claims above every resolved peer
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)
76.3
Surface (context / tools / modalities)
0.0
Freshness
79.4
  • · HF 30d downloads 9767
  • · Catalogue surface
  • · First seen 2026-07-23

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
28.5
10.3–46.6 uncertainty interval
Excluded from rank
Confidence
69%
Training support
209 models · 120 lineages
Out-of-domain check
in domain
Feature coverage
71%
Lineage-held-out error
10.0 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

Missing: deployability.independent-provider-records, deployability.measured-provider-uptime, deployability.published-provider-pricing, deployability.declared-capacity, evaluationProvenance.admitted-evaluation-observations, evaluationProvenance.capability-family-breadth, evaluationProvenance.evaluation-source-diversity, evaluationProvenance.identity-and-source-confidence, evaluationProvenance.evaluation-dataset-revisions.

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

Market activity

Venue coverage
Market Gravity
15.4
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%
76.3

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

Freshness5%
79.4

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

Specification

Context window
tokens
Max output
Inputs
Text
Outputs
Text
Tokenizer
Cached input tokens
Not offered
First seen on OpenRouter
23 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
7be56fe773e7
Parameters
34.7B
Architecture
Qwen3_5MoeForConditionalGeneration
Model type
qwen3_5_moe
Hugging Face downloads (30d)
10K
Downloads (all time)
66K
Likes
647
Repository updated
28 Jul 2026, 04:35 UTC
Base lineage
Qwen3.6-35B-A3B

Compare KAT Coder V2.5 Dev with

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Ranked neighbours

Models within 3 places of #38 on the ModelCap Index.

KAT Coder V2.5 Dev: common questions

How does KAT Coder V2.5 Dev rank among AI models?

KAT Coder V2.5 Dev holds ModelCap Index position #38 of 248 ranked language models as of 22 September 2026, with an Index score of 67.8 (interval 54.2–81.4); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does KAT Coder V2.5 Dev cost per 1M tokens?

No live API price is listed for KAT Coder V2.5 Dev in the current snapshot as of 22 September 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.

Is KAT Coder V2.5 Dev 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 Kwaipilot/KAT-Coder-V2.5-Dev on Hugging Face.

Which benchmarks has KAT Coder V2.5 Dev been evaluated on?

KAT Coder V2.5 Dev'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 22 September 2026. The evidence panel names each source and its publication date.

How does KAT Coder V2.5 Dev compare with Gemma 4 26B A4B?

KAT Coder V2.5 Dev ranks #38 (Index 67.8) and Gemma 4 26B A4B ranks #39 (Index 67.5) on the ModelCap Index as of 22 September 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was KAT Coder V2.5 Dev released?

KAT Coder V2.5 Dev first appeared in the catalogue on 23 Jul 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.