Qwen·#212 of 352 on the current board·cheaper than #192 GPT-4o (2024-08-06)
Qwen3 VL 8B Instruct is a language model from Qwen. It ranks #212 of 352 on ModelCap's current board, with an Index score of 34.4, modeled from the publisher's launch results against measured models. Its score range of 15.3–53.5 spans positions #109–#300. It is listed at $0.25 per million input tokens and $0.75 per million output tokens from one provider. It reads up to 262K tokens of context, and its weights are openly downloadable.
Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology
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.
Showing 20 of 32 rows.
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.
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
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 estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.
Not yet published: the base model it derives from, 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 Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
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.
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.
qwen/qwen3-vl-8b-instructOpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
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.
Models within 3 places of #212 on the ModelCap Index.
Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).
The same publisher's other current models with a public Index position.
Qwen3 VL 8B Instruct holds ModelCap Index position #212 of 352 ranked language models as of 6 November 2026, with an Index score of 34.4 (interval 15.3–53.5); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
Qwen3 VL 8B Instruct is listed at $0.25 per 1M input tokens and $0.75 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.875 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.
Qwen3 VL 8B Instruct has a published context window of 262K tokens (262,144). The snapshot lists a 235,929 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
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 Qwen/Qwen3-VL-8B-Instruct on Hugging Face.
One provider serves Qwen3 VL 8B Instruct through OpenRouter as of 6 November 2026: Parasail. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Qwen3 VL 8B Instruct'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.
Qwen3 VL 8B Instruct first appeared in the catalogue on 14 Oct 2025. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.