Ternary Bonsai 4B vs Grok Build 0.1

At a Glance

Compare
Intelligence, Cost, and Efficiency
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#1 of 44$0.0020 per LiveBench case
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$1.00Xai · Sep 3, 2026
Output priceFrom · USD / 1M tokensNot reported$2.00Xai · Sep 3, 2026
Context windowMaximum documented tokens33K256K
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

FieldTernary Bonsai 4BGrok Build 0.1
DeveloperPrismMLxAI
FamilyBonsai 4bGrok Build
ModelTernary Bonsai 4BGrok Build 0.1
VersionTernary Bonsai 4BGrok Build 0.1
Lifecycleactivepreview
Released2026-04-182026-05-29
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window33K256K
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 width1.58 bits per weightUnknown
Weight size1.07 GBUnknown
Weight formatTernary Q2_0Unknown

Ternary Bonsai 4B Capabilities

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

Grok Build 0.1 Capabilities

chatgenerationreasoningstructured outputstools
Serving providers1
Canonical IDxai/grok-build-0.1

Primary Evidence

Sources and Freshness

Questions

Ternary Bonsai 4B vs Grok Build 0.1 FAQs

Is Ternary Bonsai 4B or Grok Build 0.1 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Ternary Bonsai 4B and Grok Build 0.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Ternary Bonsai 4B or Grok Build 0.1?+

Only Grok Build 0.1 has a directly sourced input price: $1.00 per million tokens. Only Grok Build 0.1 has a directly sourced output price: $2.00 per million tokens.

Which has a larger context window, Ternary Bonsai 4B or Grok Build 0.1?+

Grok Build 0.1 has the larger sourced context window. Ternary Bonsai 4B supports 33K and Grok Build 0.1 supports 256K.

Which performs better in benchmarks, Ternary Bonsai 4B or Grok Build 0.1?+

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

Can Ternary Bonsai 4B or Grok Build 0.1 be self-hosted?+

Ternary Bonsai 4B is the only model in this pair currently marked as self-hostable. Ternary Bonsai 4B is open weight; Grok Build 0.1 is not marked open weight.

Can Ternary Bonsai 4B and Grok Build 0.1 understand images?+

Ternary Bonsai 4B is not documented with image input; Grok Build 0.1 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Ternary Bonsai 4B or Grok Build 0.1?+

Neither has a larger sourced maximum output. Ternary Bonsai 4B is — and Grok Build 0.1 is —.

Do Ternary Bonsai 4B and Grok Build 0.1 support reasoning and tool use?+

Ternary Bonsai 4B: none of these features are definitively sourced. Grok Build 0.1: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Ternary Bonsai 4B or Grok Build 0.1?+

Ternary Bonsai 4B has 0 sourced provider routes; Grok Build 0.1 has 1, so Grok Build 0.1 has broader tracked availability.

Which offers better value, Ternary Bonsai 4B or Grok Build 0.1?+

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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