How does Nex-N2-Pro rank among AI models?
Nex-N2-Pro is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
Nex AGI·nex-agi/nex-n2-pro
Nex-N2-Pro is ModelCap archive rank #56 (Modeled · peer benchmarks), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.
Nex-N2-Pro has a published context limit of 262K tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.
Nex-N2-Pro weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.
Snapshot facts · download the public dataset · methodology
ModelCap Index · All-versions archive
73.3#56
Estimated · 35% support · score interval 65.9–80.7
No admitted evaluation publication timestamp yet
Superseded by Nex-N2.5-Pro. It no longer holds a current-board position; its all-versions archive rank is #56.
Input
Self-hosted
weights only · no listed API price
Output
Self-hosted
weights only · no listed API price
Context
262K
tokens
Providers
0
endpoints
Gateway spend
—
latest · Vercel share
Providers
Uptime measured over the last 30 minutesNo provider is currently serving this model.
Reported evaluation leads (1)
Not independent measurementStructured 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.
Other versions (1)
ModelCap Index · All-versions archive
Methodology73.3
Modeled · peer benchmarks · calibrated architecture-and-release-era fallback from static public metadata
All-versions archive
#56
- Public rank basis
- Modeled · peer benchmarks (architecture)
- Index support
- 35.0% · limited
- Index interval
- 65.9–80.7
- 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-pro · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata nex-agi/Nex-N2-Pro@e7e4a4a29eb46a41a730d0b283ec5af0f16185d9 (not the evaluation revision)
- Index observations used
- 0
- Qualified Index evidence point
- 73.3
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
- 73.3 ± 5.8
- Independent share
- 0%
- Shrink toward corpus
- -1.3
- Peer ceiling share
- 0%
- Optimism haircut
- None required · cross lab probe, 10 probes
- Method
- precision-weighted-v1
- · Launch card row deepswe: inside the resolved peer range
- · Launch card row gpqa-diamond: inside the resolved peer range
- · Launch card row ifeval: inside the resolved peer range
- · Launch card row swe-bench-pro: inside the resolved peer range
- · Launch card row swe-bench-verified: inside the resolved peer range
- · Launch card row terminal-bench-2-1: inside the resolved peer range
- · Launch card row toolathlon: 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)
- 60.0
- Surface (context / tools / modalities)
- 90.3
- Freshness
- 66.9
- · HF 30d downloads 956
- · Catalogue: context 262144, reasoning, tools, modalities Text/Image
- · First seen 2026-06-08
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 policy68.5
52.9–84.1 uncertainty interval
- Confidence
- 77%
- Training support
- 209 models · 120 lineages
- Out-of-domain check
- in domain
- Feature coverage
- 100%
- 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 index54.2
partial · 56% metadata coverage
- Artifact reproducibility
- 85.0
- Access & legal clarity
- 100.0
- Deployability
- 29.0
- Evaluation provenance
- 0.0
Missing: artifactReproducibility.base-lineage, deployability.independent-provider-records, deployability.measured-provider-uptime, deployability.published-provider-pricing, 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
- 12.3
- 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
- Liquidity25%
- 0.0
- Open reach15%
- 60.0
- Freshness5%
- 66.9
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
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
- $0.025 / 1M
- First seen on OpenRouter
- 8 Jun 2026
Capabilities
- Supported: Reasoning
- 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
- e7e4a4a29eb4
- Parameters
- 396.8B
- Architecture
- Qwen3_5MoeForConditionalGeneration
- Model type
- qwen3_5_moe
- Hugging Face downloads (30d)
- 956
- Downloads (all time)
- 12K
- Likes
- 376
- Repository
- nex-agi/Nex-N2-Pro
- Repository updated
- 11 Jun 2026, 09:43 UTC
Benchmark leaderboards featuring Nex-N2-Pro
All leaderboardsNex-N2-Pro: common questions
How much does Nex-N2-Pro cost per 1M tokens?
No live API price is listed for Nex-N2-Pro in the current snapshot as of 22 September 2026 because no serving endpoint is published. ModelCap shows a price only when a provider currently lists one.
What is the context window of Nex-N2-Pro?
Nex-N2-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-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-Pro on Hugging Face.
Which benchmarks has Nex-N2-Pro been evaluated on?
Nex-N2-Pro has published results on 2 public boards tracked by ModelCap as of 22 September 2026: AA τ²-Bench Telecom 81.6% (#122 of 436) and AA Humanity's Last Exam 33.7% (#95 of 615). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
When was Nex-N2-Pro released?
Nex-N2-Pro first appeared in the catalogue on 8 Jun 2026. It has since been superseded by Nex-N2.5-Pro. Rank and price movements since then are recorded on the site's changes feed.