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ModelCap

ERNIE 5.5 Flash Base

Official publisher releaseRestricted license1.3d #127 → #127

Baidu·#127 of 352 on the current board

ERNIE 5.5 Flash Base is a language model from Baidu. It ranks #127 of 352 on ModelCap's current board, with an Index score of 51.2, modeled from the publisher's launch results against measured models. Its score range of 32.1–70.3 spans positions #43–#225. Its weights are downloadable under a use-restricted licence.

Figures as of 6 Nov 2026, 14:10 UTC · download the public dataset · methodology

ModelCap Index · Current board
51.2#127
Modeled from the publisher's launch results against measured models · range 32.1–70.3
Market Gravity
12.2
Secondary market signal

OpenRouter endpoint status could not be refreshed. This model is not treated as currently served until a successful observation arrives.

Input
Unlisted
no listed API price
Output
Unlisted
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
51.2
Modeled from the publisher's launch results against measured models
Current board
#127 of 352
Score range
32.1–70.3
Rank range
#43–#225
Technical details
Public rank basis
Modeled · peer benchmarks (architecture)
Evidence label
Modeled · peer benchmarks · 3 reported rows against measured corpus ladders (61%); global-corpus-prior over 210 held-out anchors (39%); shrunk 0.8 up toward the measured corpus
Index support
15.1% · limited
Identity binding
Exact catalogue product · baidu/baidu/ERNIE-5.5-Flash-Base/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata baidu/ERNIE-5.5-Flash-Base@028544b2ffceea189b2d8768ed2b9d09b06f2343 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
51.2
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
51.2 ± 14.9
Independent share
0%
Shrink toward corpus
+0.8
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Corpus ladder · not independent
3 reported rows against measured corpus ladders
50.4 ± 19.161%
Publisher corpus prior · not independent
global-corpus-prior over 210 held-out anchors
52.5 ± 23.839%
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)
—
Surface (context / tools / modalities)
0.0
Freshness
94.0
  • · Catalogue surface
  • · First seen 2026-10-21

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
32.7
17.0–48.4 uncertainty interval
Excluded from rank
Confidence
73%
Training support
221 models · 129 lineages
Out-of-domain check
in domain
Feature coverage
71%
Lineage-held-out error
8.3 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
46.4
partial · 52% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
92.5
Deployability
8.0
Evaluation provenance
0.0

Not yet published: the base model it derives from, 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
12.2
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%
50.0

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

Freshness5%
94.0

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

Specification

Model ID
baidu/ERNIE-5.5-Flash-Base
Declared output cap
Unknown

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Cached input tokens
Not offered
First seen on OpenRouter
21 Oct 2026

Capabilities

  • Not supported: Reasoning
  • Not supported: Tool use
  • Not supported: Structured output
  • Not supported: Response format
  • Not supported: Moderated

Weights & access

Restricted license. Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment.

Access
Restricted license
Pinned revision
028544b2ffce
Parameters
286.2B
Architecture
Ernie5_5_MoeForCausalLM
Model type
ernie5_5_moe
Hugging Face downloads (30d)
526
Downloads (all time)
526
Likes
202
Repository updated
5 Nov 2026, 06:33 UTC

Alternatives to ERNIE 5.5 Flash Base, by the numbers

Ranked neighbours

Models within 3 places of #127 on the ModelCap Index.

ERNIE 5.5 Flash Base: common questions

How does ERNIE 5.5 Flash Base rank among AI models?

ERNIE 5.5 Flash Base holds ModelCap Index position #127 of 352 ranked language models as of 6 November 2026, with an Index score of 51.2 (interval 32.1–70.3); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does ERNIE 5.5 Flash Base cost per 1M tokens?

No live API price is listed for ERNIE 5.5 Flash Base in the current snapshot as of 6 November 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.

Is ERNIE 5.5 Flash Base open-weight?

Restricted license (ernie-5.5-flash-base-model-license-v1.0). Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment. The repository is baidu/ERNIE-5.5-Flash-Base on Hugging Face.

Which benchmarks has ERNIE 5.5 Flash Base been evaluated on?

ERNIE 5.5 Flash Base'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 6 November 2026. The evidence panel names each source and its publication date.

When was ERNIE 5.5 Flash Base released?

ERNIE 5.5 Flash Base first appeared in the catalogue on 21 Oct 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.