PaddleOCR VL 1.5 vs Inkling

At a Glance

Compare
InklingThinking Machines Lab
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#34 of 4645.4 score · 3/3 sources · complete
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#18 of 44$0.090 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#28 of 3848.1 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.95Deepinfra · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$4.05Deepinfra · Sep 22, 2026
Context windowMaximum documented tokens131K1,049K
Model facts checkedAug 28, 2026View model evidence →Sep 3, 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-1.5Inkling
DeveloperBaiduThinking Machines Lab
FamilyPaddleocr VL 1 5Inkling
ModelPaddleOCR-VL-1.5Inkling
VersionPaddleOCR-VL-1.5Inkling
Lifecycleactiveactive
Released2026-01-292026-07-15
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Video, Audio
Output modalitiesTextText
Context window131K1,049K
Total parameters958.6M975B
Active parametersUnknown41B
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownDeepinfra (Standard), Fireworks Ai (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitieschat, generationagents, chat, coding, generation, reasoning, tools, vision

PaddleOCR VL 1.5 Capabilities

chatgeneration
Serving providers0
Canonical IDPaddlePaddle/PaddleOCR-VL-1.5

Inkling Capabilities

agentschatcodinggenerationreasoningtoolsvision
Serving providers4
Canonical IDthinkingmachines/Inkling

Primary Evidence

Sources and Freshness

Questions

PaddleOCR VL 1.5 vs Inkling FAQs

Is PaddleOCR VL 1.5 or Inkling better for coding?+

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

Which is cheaper, PaddleOCR VL 1.5 or Inkling?+

Only Inkling has a directly sourced input price: $0.95 per million tokens. Only Inkling has a directly sourced output price: $4.05 per million tokens.

Which has a larger context window, PaddleOCR VL 1.5 or Inkling?+

Inkling has the larger sourced context window. PaddleOCR VL 1.5 supports 131K and Inkling supports 1,049K.

Which performs better in benchmarks, PaddleOCR VL 1.5 or Inkling?+

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 Inkling be self-hosted?+

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

Can PaddleOCR VL 1.5 and Inkling understand images?+

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

Which can generate longer answers, PaddleOCR VL 1.5 or Inkling?+

Neither has a larger sourced maximum output. PaddleOCR VL 1.5 is — and Inkling is —.

Do PaddleOCR VL 1.5 and Inkling support reasoning and tool use?+

PaddleOCR VL 1.5: image input. Inkling: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, PaddleOCR VL 1.5 or Inkling?+

PaddleOCR VL 1.5 has 0 sourced provider routes; Inkling has 4, so Inkling has broader tracked availability.

Which offers better value, PaddleOCR VL 1.5 or Inkling?+

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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