Gemini 3.8 Flash vs Bonsai 4B

At a Glance

Compare
Gemini 3.8 FlashGoogle DeepMind
Bonsai 4BPrismML
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#8 of 4682.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 54.7–88.0UnrankedNot in the 46-model eligible cohort
CostLower is better · Published-token output estimate#26 of 44$0.160 per LiveBench caseUnrankedNot in the 44-model eligible cohort
EfficiencyHigher is better · MM Efficiency v1.5#8 of 3860.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.7–63.4UnrankedNot in the 38-model eligible cohort
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.75Google AI · Sep 2, 2026Not reported
Output priceFrom · USD / 1M tokens$3.75Google AI · Sep 2, 2026Not reported
Context windowMaximum documented tokens1,049K33K
Model facts checkedSep 2, 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

FieldGemini 3.8 FlashBonsai 4B
DeveloperGoogle DeepMindPrismML
FamilyGemini 3Bonsai 4b
ModelGemini 3.8 FlashBonsai 4B
VersionGemini 3.8 FlashBonsai 4B
Lifecycleactiveactive
Released2026-09-022026-03-29
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText
Output modalitiesTextText
Context window1,049K33K
Total parametersUnknown4B
Active parametersUnknownUnknown
LicenseUnknownapache-2.0
Open weightsNoYes
API availableYesNo
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Unknown
Capabilitieschat, code_execution, computer_use, generation, reasoning, structured_outputs, toolschat, generation
Effective bit widthUnknown1 bit per weight
Weight sizeUnknown0.57 GB
Weight formatUnknownBinary Q1_0

Gemini 3.8 Flash Capabilities

chatcode executioncomputer usegenerationreasoningstructured outputstools
Serving providers2
Canonical IDgoogle-deepmind/gemini-3.8-flash

Bonsai 4B Capabilities

chatgeneration
Serving providers0
Canonical IDprism-ml/Bonsai-4B

Primary Evidence

Sources and Freshness

Questions

Gemini 3.8 Flash vs Bonsai 4B FAQs

Is Gemini 3.8 Flash or Bonsai 4B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.8 Flash and Bonsai 4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini 3.8 Flash or Bonsai 4B?+

Only Gemini 3.8 Flash has a directly sourced input price: $0.75 per million tokens. Only Gemini 3.8 Flash has a directly sourced output price: $3.75 per million tokens.

Which has a larger context window, Gemini 3.8 Flash or Bonsai 4B?+

Gemini 3.8 Flash has the larger sourced context window. Gemini 3.8 Flash supports 1,049K and Bonsai 4B supports 33K.

Which performs better in benchmarks, Gemini 3.8 Flash or Bonsai 4B?+

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

Can Gemini 3.8 Flash or Bonsai 4B be self-hosted?+

Bonsai 4B is the only model in this pair currently marked as self-hostable. Gemini 3.8 Flash is not marked open weight; Bonsai 4B is open weight.

Can Gemini 3.8 Flash and Bonsai 4B understand images?+

Gemini 3.8 Flash is documented with image input; Bonsai 4B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini 3.8 Flash or Bonsai 4B?+

Neither has a larger sourced maximum output. Gemini 3.8 Flash is 66K and Bonsai 4B is —.

Do Gemini 3.8 Flash and Bonsai 4B support reasoning and tool use?+

Gemini 3.8 Flash: reasoning, tool calling, and image input. Bonsai 4B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini 3.8 Flash or Bonsai 4B?+

Gemini 3.8 Flash has 2 sourced provider routes; Bonsai 4B has 0, so Gemini 3.8 Flash has broader tracked availability.

Which offers better value, Gemini 3.8 Flash or Bonsai 4B?+

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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