PaddleOCR VL 1.5 vs Bonsai 8B

At a Glance

Compare
Bonsai 8BPrismML
Pricing and Limits
Context windowMaximum documented tokens131K66K
Model facts checkedAug 28, 2026View model evidence →Sep 18, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldPaddleOCR-VL-1.5Bonsai 8B
DeveloperBaiduPrismML
FamilyPaddleocr VL 1 5Bonsai 8b
ModelPaddleOCR-VL-1.5Bonsai 8B
VersionPaddleOCR-VL-1.5Bonsai 8B
Lifecycleactiveactive
Released2026-01-292026-03-18
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window131K66K
Total parameters958.6M8.2B
Active parametersUnknownUnknown
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableUnknownNo
Self-hostableYesYes
Provider accessUnknownUnknown
Capabilitieschat, generationchat, generation
Effective bit widthUnknown1 bit per weight
Weight sizeUnknown1.16 GB
Weight formatUnknownBinary Q1_0

PaddleOCR VL 1.5 Capabilities

chatgeneration
Serving providers0
Canonical IDPaddlePaddle/PaddleOCR-VL-1.5

Bonsai 8B Capabilities

chatgeneration
Serving providers0
Canonical IDprism-ml/Bonsai-8B

Primary Evidence

Sources and Freshness

Questions

PaddleOCR VL 1.5 vs Bonsai 8B FAQs

Is PaddleOCR VL 1.5 or Bonsai 8B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both PaddleOCR VL 1.5 and Bonsai 8B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, PaddleOCR VL 1.5 or Bonsai 8B?+

Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.

Which has a larger context window, PaddleOCR VL 1.5 or Bonsai 8B?+

PaddleOCR VL 1.5 has the larger sourced context window. PaddleOCR VL 1.5 supports 131K and Bonsai 8B supports 66K.

Which performs better in benchmarks, PaddleOCR VL 1.5 or Bonsai 8B?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can PaddleOCR VL 1.5 or Bonsai 8B be self-hosted?+

Both models have the same recorded self-hosting status: supported. PaddleOCR VL 1.5 is open weight; Bonsai 8B is open weight.

Can PaddleOCR VL 1.5 and Bonsai 8B understand images?+

PaddleOCR VL 1.5 is documented with image input; Bonsai 8B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, PaddleOCR VL 1.5 or Bonsai 8B?+

Neither has a larger sourced maximum output. PaddleOCR VL 1.5 is — and Bonsai 8B is —.

Do PaddleOCR VL 1.5 and Bonsai 8B support reasoning and tool use?+

PaddleOCR VL 1.5: image input. Bonsai 8B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, PaddleOCR VL 1.5 or Bonsai 8B?+

PaddleOCR VL 1.5 has 0 sourced provider routes; Bonsai 8B has 0, a tie.

Which offers better value, PaddleOCR VL 1.5 or Bonsai 8B?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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