Bonsai 4B vs Grok 4.5

At a Glance

Compare
Bonsai 4BPrismML
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#25 of 4660.1 score · 3/3 sources · complete
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#15 of 44$0.063 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#11 of 3859.2 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$2.00Xai · Sep 3, 2026
Output priceFrom · USD / 1M tokensNot reported$6.00Xai · Sep 3, 2026
Context windowMaximum documented tokens33K500K
Model facts checkedSep 18, 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

FieldBonsai 4BGrok 4.5
DeveloperPrismMLxAI
FamilyBonsai 4bGrok 4
ModelBonsai 4BGrok 4.5
VersionBonsai 4BGrok 4.5
Lifecycleactiveactive
Released2026-03-292026-07-16
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window33K500K
Total parameters4BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableNoYes
Self-hostableYesNo
Provider accessUnknownXai (Standard)
Capabilitieschat, generationchat, generation, reasoning, structured_outputs, tools
Effective bit width1 bit per weightUnknown
Weight size0.57 GBUnknown
Weight formatBinary Q1_0Unknown

Bonsai 4B Capabilities

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

Grok 4.5 Capabilities

chatgenerationreasoningstructured outputstools
Serving providers1
Canonical IDxai/grok-4.5

Primary Evidence

Sources and Freshness

Questions

Bonsai 4B vs Grok 4.5 FAQs

Is Bonsai 4B or Grok 4.5 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Bonsai 4B and Grok 4.5, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Bonsai 4B or Grok 4.5?+

Only Grok 4.5 has a directly sourced input price: $2.00 per million tokens. Only Grok 4.5 has a directly sourced output price: $6.00 per million tokens.

Which has a larger context window, Bonsai 4B or Grok 4.5?+

Grok 4.5 has the larger sourced context window. Bonsai 4B supports 33K and Grok 4.5 supports 500K.

Which performs better in benchmarks, Bonsai 4B or Grok 4.5?+

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

Can Bonsai 4B or Grok 4.5 be self-hosted?+

Bonsai 4B is the only model in this pair currently marked as self-hostable. Bonsai 4B is open weight; Grok 4.5 is not marked open weight.

Can Bonsai 4B and Grok 4.5 understand images?+

Bonsai 4B is not documented with image input; Grok 4.5 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Bonsai 4B or Grok 4.5?+

Neither has a larger sourced maximum output. Bonsai 4B is — and Grok 4.5 is —.

Do Bonsai 4B and Grok 4.5 support reasoning and tool use?+

Bonsai 4B: none of these features are definitively sourced. Grok 4.5: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Bonsai 4B or Grok 4.5?+

Bonsai 4B has 0 sourced provider routes; Grok 4.5 has 1, so Grok 4.5 has broader tracked availability.

Which offers better value, Bonsai 4B or Grok 4.5?+

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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