phi-4 vs Bonsai 27B

At a Glance

Compare
phi-4Microsoft
Bonsai 27BPrismML
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.070Deepinfra · Sep 23, 2026Not reported
Output priceFrom · USD / 1M tokens$0.14Deepinfra · Sep 23, 2026Not reported
Context windowMaximum documented tokens16K262K
Model facts checkedAug 28, 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

Fieldphi-4Bonsai 27B
DeveloperMicrosoftPrismML
FamilyPhi 4Bonsai 27b
Modelphi-4Bonsai 27B
Versionphi-4Bonsai 27B
Lifecycleactiveactive
Released2024-12-122026-07-04
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window16K262K
Total parameters14.7B27B
Active parametersUnknownUnknown
Licensemitapache-2.0
Open weightsYesYes
API availableYesNo
Self-hostableYesYes
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Unknown
Capabilitieschat, generationchat, generation, reasoning, tools, vision
Base modelUnknownQwen3.6 27B
Effective bit widthUnknown1 bit per weight
Language model sizeUnknown3.53 GiB
Weight formatUnknownBinary Q1_0

phi-4 Capabilities

chatgeneration
Serving providers3
Canonical IDmicrosoft/phi-4

Bonsai 27B Capabilities

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

Primary Evidence

Sources and Freshness

Questions

phi-4 vs Bonsai 27B FAQs

Is phi-4 or Bonsai 27B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both phi-4 and Bonsai 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, phi-4 or Bonsai 27B?+

Only phi-4 has a directly sourced input price: $0.070 per million tokens. Only phi-4 has a directly sourced output price: $0.14 per million tokens.

Which has a larger context window, phi-4 or Bonsai 27B?+

Bonsai 27B has the larger sourced context window. phi-4 supports 16K and Bonsai 27B supports 262K.

Which performs better in benchmarks, phi-4 or Bonsai 27B?+

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

Can phi-4 or Bonsai 27B be self-hosted?+

Both models have the same recorded self-hosting status: supported. phi-4 is open weight; Bonsai 27B is open weight.

Can phi-4 and Bonsai 27B understand images?+

phi-4 is not documented with image input; Bonsai 27B is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, phi-4 or Bonsai 27B?+

Neither has a larger sourced maximum output. phi-4 is — and Bonsai 27B is —.

Do phi-4 and Bonsai 27B support reasoning and tool use?+

phi-4: none of these features are definitively sourced. Bonsai 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, phi-4 or Bonsai 27B?+

phi-4 has 3 sourced provider routes; Bonsai 27B has 0, so phi-4 has broader tracked availability.

Which offers better value, phi-4 or Bonsai 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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