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Data

Data as of October 25, 2026 · How the score is built

CurrentOpen WeightNon-Reasoning

Released May 8, 2026131K contextZyphra ZAYA1-VL-8B model card

ZAYA1-VL-8B

Decision readingZAYA1-VL-8B is tracked, but not publicly ranked yet. The profile exposes 5 sourced benchmark rows and leaves unsupported fields blank until a published record exists.

Released May 8, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

Unranked

field median 50Not eligible for a public rank

Price

Self-hosted; infrastructure cost varies

input median $0.75No comparable first-party hosted token rate

Speed

Not measured

field median 96 tok/sTime to first token not measured

Context

131Ktokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Published rows are visible, but no category has enough eligible evidence for a comparative rank.

Validate before choosing

5 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.

Source-linked · 5 displayable benchmark rows

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%0 benchmarksNot measured
Not measured
CodingWeight 20%0 benchmarksNot measured
Not measured
ReasoningWeight 17%0 benchmarksNot measured
Not measured
MultimodalWeight 12%5 benchmarksVerified
Score pending
KnowledgeWeight 12%0 benchmarksNot measured
Not measured
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathWeight 5%0 benchmarksNot measured
Not measured

5 of 766 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. AgenticNot measured
  2. CodingNot measured
  3. ReasoningNot measured
  4. Multimodal5/5 verified
  5. KnowledgeNot measured
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. MathNot measured
Verified sourceProvisionalNot measured

Benchmark ledger

Multimodal opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Multimodal5 rows
Multimodal benchmark values, best verified comparison, weight, and source status
AI2D_TESTAI2D test splitScore87.5%Versus best verified row

Best verified: Qwen3.5 397B · 93.9%

Gap6.4 behindWeightDisplay only
MMMUMassive Multi-discipline Multimodal UnderstandingScore46.0%Versus best verified row

Best verified: Qwen3.5 397B · 85.0%

Gap39 behindWeightDisplay only
RealWorldQAScore65.0%Versus best verified row

Best verified: Qwen3.8-Flash-Next · 88.5%

Gap23.5 behindWeightDisplay only
CountBenchScore88.1%Versus best verified row

Best verified: Qwen3.6-27B · 97.8%

Gap9.7 behindWeightDisplay only
RefCOCO (avg)RefCOCO averageScore84.3%Versus best verified row

Best verified: Qwen3.6-27B · 92.5%

Gap8.2 behindWeightDisplay only

Bars run 0–100; the dark tick marks the best source-verified value

All 5 rows

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. May 8, 2026 · you are here

    ZAYA1-VL-8B

    Not publicly ranked · Price not listed

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Zyphra/ZAYA1-VL-8BZyphra ZAYA1-VL-8B model card
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Zyphra publishes the 8B-total, 0.7B-active vision-language model built on ZAYA1-base under Apache 2.0 on Hugging Face; the context window is inherited from the ZAYA1-8B base because the card does not publish a separate figure.
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing recordZyphra ZAYA1-VL-8B model card
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

We track ZAYA1-VL-8B, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.

ZAYA1-VL-8B is a open weight model with a 131K context window. No explicit reasoning mode is documented in this profile.

Zyphra publishes the 8B-total, 0.7B-active vision-language model built on ZAYA1-base under Apache 2.0 on Hugging Face; the context window is inherited from the ZAYA1-8B base because the card does not publish a separate figure.

Official exact-value snapshot from the ZAYA1-VL-8B Hugging Face model card (May 8, 2026). BenchLM maps AI2D, MMMU (val), RealWorldQA, CountBenchQA, and RefCOCO average onto existing lanes; ChartQA, DocVQA, InfoVQA, TextVQA, OCRBench, VQA v2, MathVista, SEED, BLINK, PixMoCount, and Point-Bench have no exact compatible lane. Provider-run rows keep the row unranked.

ZAYA1-VL-8B sits in the ZAYA1 family with ZAYA1-8B, ZAYA1-74B-Preview. 5 of 766 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Last updated October 25, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Questions

How does ZAYA1-VL-8B perform overall in AI benchmarks?

ZAYA1-VL-8B has 5 source-displayable benchmark rows, but it does not qualify for a public overall rank. The available rows remain visible by category without being converted into a site-wide score. Missing evidence stays blank instead of being estimated from an earlier model.

Is ZAYA1-VL-8B good for multimodal and grounded tasks?

ZAYA1-VL-8B has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is ZAYA1-VL-8B open source?

ZAYA1-VL-8B is an open-weight model from Zyphra. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Which sibling models are related to ZAYA1-VL-8B?

ZAYA1-VL-8B belongs to the ZAYA1 family. Related tracked variants include ZAYA1-8B, ZAYA1-74B-Preview. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.

Does ZAYA1-VL-8B have full benchmark coverage on BenchLM?

No. ZAYA1-VL-8B currently has 5 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of ZAYA1-VL-8B?

ZAYA1-VL-8B has a documented context window of 131K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

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