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.
Reported evaluation leads (10)
Not independent measurement
Structured 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.
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
39.3 ± 6.9
Independent share
0%
Shrink toward corpus
+2.7
Peer ceiling share
0%
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
Channel
Estimate
Share
Publisher corpus prior · not independent
publisher-corpus-prior over 182 held-out anchors
65.0 ± 22.3
9%
Launch card against resolved peers · not independent
launch card against 3 resolved peers on 5 rows
36.6 ± 7.2
91%
· Launch card row aime-2026-without-tools: inside the resolved peer range
· Launch card row gpqa-diamond: inside the resolved peer range
· Launch card row livecodebench-v-6: inside the resolved peer range
· Launch card row mmlu-pro: claims below every resolved peer
· Launch card row mmmu-pro: 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)
—
Liquidity (providers × uptime)
—
Open reach (HF downloads)
98.6
Surface (context / tools / modalities)
15.0
Freshness
48.3
· HF 30d downloads 3222423
· Catalogue: modalities Text/Image/Audio
· First seen 2026-03-02
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.
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%
98.6
Hugging Face 30-day downloads for open models; neutral for closed models.
Freshness5%
48.3
Time since first public availability, on a six-month half-life.
Specification
Context window
— tokens
Max output
—
Inputs
Text, Image, Audio
Outputs
Text, Image, Audio
Tokenizer
—
Cached input tokens
Not offered
First seen on OpenRouter
2 Mar 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.
gemma 4 E2B it holds ModelCap Index position #106 of 160 ranked language models as of 9 September 2026, with an Index score of 39.3 (interval 30.5–48.1); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
How much does gemma 4 E2B it cost per 1M tokens?
No live API price is listed for gemma 4 E2B it in the current snapshot as of 9 September 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.
Is gemma 4 E2B it 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 google/gemma-4-E2B-it on Hugging Face.
Which benchmarks has gemma 4 E2B it been evaluated on?
gemma 4 E2B it'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 gemma 4 E2B it compare with Nemotron 3 Super?
gemma 4 E2B it ranks #106 (Index 39.3) and Nemotron 3 Super ranks #107 (Index 38.9) 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 gemma 4 E2B it released?
gemma 4 E2B it first appeared in the catalogue on 2 Mar 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.