ERNIE 4.5 0.3B PT vs Gemini Computer Use

At a Glance

Compare
Gemini Computer UseGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$1.25Google AI · Aug 29, 2026
Output priceFrom · USD / 1M tokensNot reported$10.00Google AI · Aug 29, 2026
Context windowMaximum documented tokens131K128K
Model facts checkedAug 28, 2026View model evidence →Aug 29, 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

FieldERNIE-4.5-0.3B-PTGemini Computer Use
DeveloperBaiduGoogle DeepMind
FamilyErnie 4 5 0 3b PtGemini Tools
ModelERNIE-4.5-0.3B-PTGemini Computer Use
VersionERNIE-4.5-0.3B-PTGemini Computer Use
Lifecycleactivepreview
ReleasedUnknownUnknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window131K128K
Total parameters360.7MUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableUnknownYes
Self-hostableYesNo
Provider accessUnknownGoogle AI (Standard), Google Gemini (Standard)
Capabilitieschat, generationgeneration, reasoning, tools

ERNIE 4.5 0.3B PT Capabilities

chatgeneration
Serving providers0
Canonical IDbaidu/ERNIE-4.5-0.3B-PT

Gemini Computer Use Capabilities

generationreasoningtools
Serving providers2
Canonical IDgoogle-deepmind/gemini-2.5-computer-use-preview-10-2025

Primary Evidence

Sources and Freshness

Questions

ERNIE 4.5 0.3B PT vs Gemini Computer Use FAQs

Is ERNIE 4.5 0.3B PT or Gemini Computer Use better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE 4.5 0.3B PT and Gemini Computer Use, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, ERNIE 4.5 0.3B PT or Gemini Computer Use?+

Only Gemini Computer Use has a directly sourced input price: $1.25 per million tokens. Only Gemini Computer Use has a directly sourced output price: $10.00 per million tokens.

Which has a larger context window, ERNIE 4.5 0.3B PT or Gemini Computer Use?+

ERNIE 4.5 0.3B PT has the larger sourced context window. ERNIE 4.5 0.3B PT supports 131K and Gemini Computer Use supports 128K.

Which performs better in benchmarks, ERNIE 4.5 0.3B PT or Gemini Computer Use?+

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

Can ERNIE 4.5 0.3B PT or Gemini Computer Use be self-hosted?+

ERNIE 4.5 0.3B PT is the only model in this pair currently marked as self-hostable. ERNIE 4.5 0.3B PT is open weight; Gemini Computer Use is not marked open weight.

Can ERNIE 4.5 0.3B PT and Gemini Computer Use understand images?+

ERNIE 4.5 0.3B PT is not documented with image input; Gemini Computer Use is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, ERNIE 4.5 0.3B PT or Gemini Computer Use?+

Neither has a larger sourced maximum output. ERNIE 4.5 0.3B PT is — and Gemini Computer Use is 64K.

Do ERNIE 4.5 0.3B PT and Gemini Computer Use support reasoning and tool use?+

ERNIE 4.5 0.3B PT: none of these features are definitively sourced. Gemini Computer Use: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, ERNIE 4.5 0.3B PT or Gemini Computer Use?+

ERNIE 4.5 0.3B PT has 0 sourced provider routes; Gemini Computer Use has 2, so Gemini Computer Use has broader tracked availability.

Which offers better value, ERNIE 4.5 0.3B PT or Gemini Computer Use?+

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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