Skip to content
ModelCap

Nex-N2.5-Pro

Current board #16Official publisher releaseNewOpen weightsFree tier7d #18 → #16

Nex AGI·nex-agi/nex-n2.5-pro

Nex-N2.5-Pro is ModelCap current-board rank #16 with Index 75.8 (Modeled · peer benchmarks), from the ModelCap Index as of 9 Sept 2026, 17:56 UTC.

Nex-N2.5-Pro listed OpenRouter input price is Free per 1M tokens and listed output price is Free per 1M tokens, from OpenRouter listed prices as of 9 Sept 2026, 17:56 UTC.

Nex-N2.5-Pro has a published context limit of 262K tokens in the ModelCap catalogue as of 9 Sept 2026, 17:56 UTC.

Nex-N2.5-Pro has 1 published OpenRouter serving endpoint, from OpenRouter as of 9 Sept 2026, 17:56 UTC.

Nex-N2.5-Pro weight access is open weights, from ModelCap classification of published repository metadata as of 9 Sept 2026, 17:56 UTC.

Snapshot facts · download the public dataset · methodology

ModelCap Index · Current board
75.8#16
Estimated · 38% support · score interval 66.5–85.1
No admitted evaluation publication timestamp yet
Market Gravity
19.6Increased by 6.3
Secondary market signal
Input
Free
per 1M tokens
Output
Free
per 1M tokens
Context
262K
tokens
Providers
1
endpoint
Gateway spend
latest · Vercel share

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Nex AGIfp8FreeFree262Kfp899.44%

Other versions (1)

ModelCap Index · Current board

Methodology
75.8
Modeled · peer benchmarks · calibrated architecture-and-release-era fallback from static public metadata
Current board
#16
Public rank basis
Modeled · peer benchmarks (architecture)
Index support
38.0% · limited
Index interval
66.5–85.1
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 · nex-agi/nex-agi/nex-n2.5-pro · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata nex-agi/Nex-N2.5-Pro@937d21d8427046d51cc919bad795b9de71000635 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
75.8
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
75.8 ± 7.3
Independent share
0%
Shrink toward corpus
-2.7
Peer ceiling share
13%
Optimism haircut
None required · cross lab probe, 7 probes
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
global-corpus-prior over 178 held-out anchors
53.9 ± 22.011%
Launch card against resolved peers · not independent
launch card against 8 resolved peers on 8 rows
78.5 ± 7.789%
  • · Launch card row automationbench-v-1-0-6-5: inside the resolved peer range
  • · Launch card row deepswe-v-1-1: claims below every resolved peer
  • · Launch card row osworld-2: inside the resolved peer range
  • · Launch card row osworld-g: claims above every resolved peer
  • · Launch card row osworld-verified-8: inside the resolved peer range
  • · Launch card row swe-bench-pro: inside the resolved peer range
  • · Launch card row terminal-bench-2-1: claims below every resolved peer
  • · Launch card row toolathlon-verified: claims below 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)
18.3
Liquidity (providers × uptime)
17.8
Open reach (HF downloads)
0.7
Surface (context / tools / modalities)
90.3
Freshness
99.6
  • · OpenRouter popularity #109
  • · 1 live provider
  • · HF 30d downloads 0
  • · Catalogue: context 262144, reasoning, tools, modalities Text/Image
  • · First seen 2026-09-08

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
Estimator abstained

insufficient-artifact-metadata

Feature coverage
86%
Training support
183 models · 105 lineages

insufficient-artifact-metadata. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
53.0
partial · 59% metadata coverage
Not capability
Artifact reproducibility
30.0
Access & legal clarity
100.0
Deployability
79.9
Evaluation provenance
0.0

Missing: artifactReproducibility.architecture-and-model-type, artifactReproducibility.parameter-count, artifactReproducibility.serialized-weight-format, artifactReproducibility.base-lineage, 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
19.6
OpenRouter weekly popularity
#109 of 312

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%
18.3

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
17.8

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

Open reach15%
0.7

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

Freshness5%
99.6

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

Specification

Context window
262K tokens
Max output
236K tokens
Inputs
Text, Image
Outputs
Text
Tokenizer
Qwen3
Cached input tokens
Not offered
First seen on OpenRouter
8 Sept 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • 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
937d21d84270
Hugging Face downloads (30d)
0
Downloads (all time)
0
Likes
163
Repository updated
8 Sept 2026, 16:17 UTC

Compare Nex-N2.5-Pro with

Pick any model

Alternatives to Nex-N2.5-Pro, by the numbers

Ranked neighbours

Models within 3 places of #16 on the ModelCap Index.

Other ranked Nex AGI models

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

Nex-N2.5-Pro: common questions

How does Nex-N2.5-Pro rank among AI models?

Nex-N2.5-Pro holds ModelCap Index position #16 of 126 ranked language models as of 9 September 2026, with an Index score of 75.8 (interval 66.5–85.1); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Nex-N2.5-Pro cost per 1M tokens?

Nex-N2.5-Pro is listed at Free per 1M input tokens and Free per 1M output tokens as of 9 September 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh; at least one provider lists a free tier. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply Free total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Nex-N2.5-Pro?

Nex-N2.5-Pro has a published context window of 262K tokens (262,144) and a maximum output of 236K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.

Is Nex-N2.5-Pro 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 nex-agi/Nex-N2.5-Pro on Hugging Face.

Which API providers serve Nex-N2.5-Pro?

One provider serves Nex-N2.5-Pro through OpenRouter as of 9 September 2026: Nex AGI. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Nex-N2.5-Pro been evaluated on?

Nex-N2.5-Pro'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 9 September 2026. The evidence panel names each source and its publication date.

How does Nex-N2.5-Pro compare with Claude Sonnet 5?

Nex-N2.5-Pro ranks #16 (Index 75.8) and Claude Sonnet 5 ranks #17 (Index 75.5) on the ModelCap Index as of 9 September 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was Nex-N2.5-Pro released?

Nex-N2.5-Pro first appeared in the catalogue on 8 Sept 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.