CohereLanguage model
Aya Vision 8B
Aya Vision 8B has no overall index value yet because there are too few independent benchmark results.
27out of 100+3 vs. last month
based on search, usage and attention
Summary
Aya Vision 8B is the compact open vision-language variant in the Aya Vision family. It combines text and image inputs with multilingual visual understanding for OCR, captions, visual questions, and summaries. The model card places it in the same research line as Aya Expanse, extended with a visual adapter.
Aya Vision 8B has 8 billion parameters, compared with 32 billion in Aya Vision 32B. Its context window is 16,000 tokens. Responses remain text-based. The weights use CC BY-NC 4.0 for non-commercial use.
All benchmark results
Every published result with its source, test setup and comparison models.
Show all 92 published benchmark results
Page 1 of 8
Measurements without matching peer values
These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.
AyaVisionBench win rate vs Gemini-Flash 1.5-8B (Show measurement, test conditions, and source)
- Source value
- 55.8
- Score
- 55.8
- Metric
- pairwise win rate
- Unit
- %
- Benchmark version
- AyaVisionBench; 23-language average
- Category
- multimodal
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Cohere for AI Aya Vision win-rate figure
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Vendor-reported result. Exact Aya Vision 8B release model. The figure compares pairwise win, loss, and tie rates on AyaVisionBench; the article says results are averaged across 23 languages. The card identifies Claude 3.7 Sonnet as the judge. Prompt details and the number of judgments are not stated.
AyaVisionBench win rate vs Llama 3.2 11B (Show measurement, test conditions, and source)
- Source value
- 72.1
- Score
- 72.1
- Metric
- pairwise win rate
- Unit
- %
- Benchmark version
- AyaVisionBench; 23-language average
- Category
- multimodal
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Cohere for AI Aya Vision win-rate figure
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Vendor-reported result. Exact Aya Vision 8B release model. The figure compares pairwise win, loss, and tie rates on AyaVisionBench; the article says results are averaged across 23 languages. The card identifies Claude 3.7 Sonnet as the judge. Prompt details and the number of judgments are not stated.
AyaVisionBench win rate vs Qwen2.5-VL 7B (Show measurement, test conditions, and source)
- Source value
- 52.1
- Score
- 52.1
- Metric
- pairwise win rate
- Unit
- %
- Benchmark version
- AyaVisionBench; 23-language average
- Category
- multimodal
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Cohere for AI Aya Vision win-rate figure
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Vendor-reported result. Exact Aya Vision 8B release model. The figure compares pairwise win, loss, and tie rates on AyaVisionBench; the article says results are averaged across 23 languages. The card identifies Claude 3.7 Sonnet as the judge. Prompt details and the number of judgments are not stated.
AyaVisionBench win rate vs Molmo 7B (Show measurement, test conditions, and source)
- Source value
- 78.6
- Score
- 78.6
- Metric
- pairwise win rate
- Unit
- %
- Benchmark version
- AyaVisionBench; 23-language average
- Category
- multimodal
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Cohere for AI Aya Vision win-rate figure
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Vendor-reported result. Exact Aya Vision 8B release model. The figure compares pairwise win, loss, and tie rates on AyaVisionBench; the article says results are averaged across 23 languages. The card identifies Claude 3.7 Sonnet as the judge. Prompt details and the number of judgments are not stated.
AyaVisionBench win rate vs Pixtral 12B (Show measurement, test conditions, and source)
- Source value
- 49.2
- Score
- 49.2
- Metric
- pairwise win rate
- Unit
- %
- Benchmark version
- AyaVisionBench; 23-language average
- Category
- multimodal
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Cohere for AI Aya Vision win-rate figure
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Vendor-reported result. Exact Aya Vision 8B release model. The figure compares pairwise win, loss, and tie rates on AyaVisionBench; the article says results are averaged across 23 languages. The card identifies Claude 3.7 Sonnet as the judge. Prompt details and the number of judgments are not stated.
AyaVisionBench win rate vs Pangea 7B (Show measurement, test conditions, and source)
- Source value
- 70
- Score
- 70
- Metric
- pairwise win rate
- Unit
- %
- Benchmark version
- AyaVisionBench; 23-language average
- Category
- multimodal
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Cohere for AI Aya Vision win-rate figure
- Status
- active
- Retrieved at
- 2026-10-15
- Methodology
- Vendor-reported result. Exact Aya Vision 8B release model. The figure compares pairwise win, loss, and tie rates on AyaVisionBench; the article says results are averaged across 23 languages. The card identifies Claude 3.7 Sonnet as the judge. Prompt details and the number of judgments are not stated.
G-MMLU Lite (Show measurement, test conditions, and source)
- Source value
- 62.52
- Score
- 62.52
- Metric
- accuracy
- Unit
- %
- Category
- language-understanding
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Aya Vision technical report, arXiv:2505.08751v1
- Status
- active
- Retrieved at
- 2026-10-17
- Methodology
- Vendor-reported result. Aya Vision 8B, paper text-only benchmark table. The table does not state a prompt-shot count.
MGSM (Show measurement, test conditions, and source)
- Source value
- 76.42
- Score
- 76.42
- Metric
- accuracy
- Unit
- %
- Category
- mathematical-reasoning
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Aya Vision technical report, arXiv:2505.08751v1
- Status
- active
- Retrieved at
- 2026-10-17
- Methodology
- Vendor-reported result. Aya Vision 8B, paper text-only benchmark table. The table does not state a prompt-shot count.
IFEval (Show measurement, test conditions, and source)
- Source value
- 82.78
- Score
- 82.78
- Metric
- accuracy
- Unit
- %
- Category
- language-understanding
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Aya Vision technical report, arXiv:2505.08751v1
- Status
- active
- Retrieved at
- 2026-10-17
- Methodology
- Vendor-reported result. Aya Vision 8B, paper text-only benchmark table. The table does not state a prompt-shot count.
m-ArenaHard win rate vs Llama 3.2 11B Vision (Show measurement, test conditions, and source)
- Source value
- 63.4
- Score
- 63.4
- Metric
- pairwise win rate
- Unit
- %
- Category
- open-ended-generation
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Aya Vision technical report, arXiv:2505.08751v1
- Status
- active
- Retrieved at
- 2026-10-17
- Methodology
- Vendor-reported result. m-ArenaHard, pairwise text-only evaluation, average across 23 languages; GPT-4o-2024-11-20 judge.
m-ArenaHard win rate vs Pixtral 12B (Show measurement, test conditions, and source)
- Source value
- 44
- Score
- 44
- Metric
- pairwise win rate
- Unit
- %
- Category
- open-ended-generation
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Aya Vision technical report, arXiv:2505.08751v1
- Status
- active
- Retrieved at
- 2026-10-17
- Methodology
- Vendor-reported result. m-ArenaHard, pairwise text-only evaluation, average across 23 languages; GPT-4o-2024-11-20 judge.
Cedar accuracy, multimodal (reported Avg.) (Show measurement, test conditions, and source)
- Source value
- 32.89
- Score
- 32.89
- Metric
- standard accuracy
- Unit
- %
- Category
- multilingual-cultural-reasoning
- Direction
- Higher is better
- Source type
- independent-evaluator
- Evaluator
- Cedar independent evaluation, arXiv:2601.13024v1
- Status
- disputed
- Retrieved at
- 2026-10-17
- Methodology
- Independent evaluation. Aya Vision 8B exact CohereLabs checkpoint, Cedar Table 1 Avg. column, multimodal subset; paper defines Avg. as macro-average across languages.
- Context
- The paper calls the aggregate a macro-average across languages, but the published aggregate differs from the mean of the displayed non-missing language cells. Kept as disputed, not a reconciled score.
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Popularity compared
How often the model is searched for, used and mentioned, compared with every model of its category.
Popularity index
The 100 most popular models of this category, 0 to 100, higher is more popular
20 of 101 models
As of November 2026 · Source: gradually.ai popularity index
Over time
Weekly values from October 18, 2026 to November 7, 2026
Aya Vision 8BClaude Opus 4.7 27MiniMax-M2.7-highspeed 27Tiny Aya Fire 27Falcon 3 7B 26
Method changes in the timeline, a jump at these points is no market event:
- 1November 1, 2026: Value only with search or usage data, 30-day attention
What is gaining popularity right now, across models, vendors, harnesses and AI subscriptions, is collected in All AI trends.
Similar models
More models of the same kind as Aya Vision 8B, chosen by model line, developer, size, price and release date.
All specifications
Architecture
Input and output
Watermarking and provenance
AI watermarking refers to invisible signals embedded in the output. Visible marks and provenance metadata are listed separately. Unknown means there is insufficient evidence for that particular field.
- AI watermarking
- Unknown
- no source
- Watermarking technique
- Not known
- no source
Licence and access
Frequently asked questions about Aya Vision 8B
How large is the context window of Aya Vision 8B?
16,000 tokens. That is how much text Aya Vision 8B reads at once, about 20 A4 pages.
Page count as a rule of thumb from Artificial Analysis
Can I run Aya Vision 8B locally?
Yes, the weights are open.
Stated by Cohere
- Open weights
- yes
- License
- CC BY-NC-4.0
- Parameters
- 8B
- active per token
- n/a
Sources and data date
Show all 29 sources
Benchmark sources at a glance
Which independent evaluators tested this model. This is coverage, not a quality ranking.
No active result from the reviewed external evaluators can currently be attributed to this model. Other source evidence remains available below.
Without vendor claims and historical or disputed results; those stay labelled in the single values.