Bonsai 27B vs Ternary Bonsai 2 27B

At a Glance

Compare
Bonsai 27BPrismML
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.075Openrouter · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$0.50Openrouter · Sep 22, 2026
Context windowMaximum documented tokens262K262K
Model facts checkedSep 18, 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

FieldBonsai 27BTernary Bonsai 2 27B
DeveloperPrismMLPrismML
FamilyBonsai 27bBonsai 2
ModelBonsai 27BTernary Bonsai 2 27B
VersionBonsai 27BTernary Bonsai 2 27B
Lifecycleactiveactive
Released2026-07-042026-09-17
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image
Output modalitiesTextText
Context window262K262K
Total parameters27B27.4B
Active parametersUnknownUnknown
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableNoYes
Self-hostableYesYes
Provider accessUnknownOpenrouter (Standard)
Capabilitieschat, generation, reasoning, tools, visionchat, generation, reasoning, tools, vision
Base modelQwen3.6 27BQwen3.8 27B
Effective bit width1 bit per weight1.76 bits per weight
Language model size3.53 GiB5.93 GB
Weight formatBinary Q1_0Ternary g128 with FP16 group scales

Bonsai 27B Capabilities

chatgenerationreasoningtoolsvision
Serving providers0
Canonical IDprism-ml/Bonsai-27B

Ternary Bonsai 2 27B Capabilities

chatgenerationreasoningtoolsvision
Serving providers1
Canonical IDprism-ml/Ternary-Bonsai-2-27B

Primary Evidence

Sources and Freshness

Questions

Bonsai 27B vs Ternary Bonsai 2 27B FAQs

Is Bonsai 27B or Ternary Bonsai 2 27B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Bonsai 27B and Ternary Bonsai 2 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Bonsai 27B or Ternary Bonsai 2 27B?+

Only Ternary Bonsai 2 27B has a directly sourced input price: $0.075 per million tokens. Only Ternary Bonsai 2 27B has a directly sourced output price: $0.50 per million tokens.

Which has a larger context window, Bonsai 27B or Ternary Bonsai 2 27B?+

Neither model has a larger sourced context window in this comparison. Bonsai 27B is 262K and Ternary Bonsai 2 27B is 262K.

Which performs better in benchmarks, Bonsai 27B or Ternary Bonsai 2 27B?+

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

Can Bonsai 27B or Ternary Bonsai 2 27B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Bonsai 27B is open weight; Ternary Bonsai 2 27B is open weight.

Can Bonsai 27B and Ternary Bonsai 2 27B understand images?+

Bonsai 27B is documented with image input; Ternary Bonsai 2 27B is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Bonsai 27B or Ternary Bonsai 2 27B?+

Neither has a larger sourced maximum output. Bonsai 27B is — and Ternary Bonsai 2 27B is —.

Do Bonsai 27B and Ternary Bonsai 2 27B support reasoning and tool use?+

Bonsai 27B: reasoning, tool calling, and image input. Ternary Bonsai 2 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Bonsai 27B or Ternary Bonsai 2 27B?+

Bonsai 27B has 0 sourced provider routes; Ternary Bonsai 2 27B has 1, so Ternary Bonsai 2 27B has broader tracked availability.

Which offers better value, Bonsai 27B or Ternary Bonsai 2 27B?+

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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