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
60.6 ± 9.5
Independent share
0%
Shrink toward corpus
-1.4
Peer ceiling share
75%
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
Channel
Estimate
Share
Publisher corpus prior · not independent
global-corpus-prior over 180 held-out anchors
54.0 ± 22.5
18%
Launch card against resolved peers · not independent
launch card against 2 resolved peers on 4 rows
62.0 ± 10.5
82%
· Launch card row aime-2025: claims above every resolved peer
· Launch card row hmmt-2025: claims above every resolved peer
· Launch card row livecodebench: claims above every resolved peer
· Launch card row mmmu: 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)
74.3
Surface (context / tools / modalities)
15.0
Freshness
40.2
· HF 30d downloads 18822
· Catalogue: modalities Text/Image
· First seen 2026-01-13
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%
74.3
Hugging Face 30-day downloads for open models; neutral for closed models.
Freshness5%
40.2
Time since first public availability, on a six-month half-life.
Specification
Context window
— tokens
Max output
—
Inputs
Text, Image
Outputs
Text
Tokenizer
—
Cached input tokens
Not offered
First seen on OpenRouter
13 Jan 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.
Step3 VL 10B holds ModelCap Index position #44 of 156 ranked language models as of 9 September 2026, with an Index score of 60.6 (interval 48.4–72.7); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
How much does Step3 VL 10B cost per 1M tokens?
No live API price is listed for Step3 VL 10B 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 Step3 VL 10B 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 stepfun-ai/Step3-VL-10B on Hugging Face.
Which benchmarks has Step3 VL 10B been evaluated on?
Step3 VL 10B has published results on 2 public boards tracked by ModelCap as of 9 September 2026: AA τ²-Bench Telecom 16.1% (#374 of 436) and AA Humanity's Last Exam 10.8% (#266 of 603). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
How does Step3 VL 10B compare with Kimi K2.7 Code?
Step3 VL 10B ranks #44 (Index 60.6) and Kimi K2.7 Code ranks #45 (Index 60.0) 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 Step3 VL 10B released?
Step3 VL 10B first appeared in the catalogue on 13 Jan 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.