ERNIE X1.1 vs Ternary Bonsai 2 27B

At a Glance

Compare
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 tokens66K262K
Model facts checkedAug 29, 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

FieldERNIE X1.1Ternary Bonsai 2 27B
DeveloperBaiduPrismML
FamilyErnie X1Bonsai 2
ModelERNIE X1.1Ternary Bonsai 2 27B
VersionERNIE X1.1Ternary Bonsai 2 27B
Lifecycleactiveactive
Released2025-09-262026-09-17
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window66K262K
Total parametersUnknown27.4B
Active parametersUnknownUnknown
LicenseUnknownapache-2.0
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessBaidu Qianfan (Standard)Openrouter (Standard)
Capabilitiesagents, chat, reasoning, search, toolschat, generation, reasoning, tools, vision
Base modelUnknownQwen3.8 27B
Effective bit widthUnknown1.76 bits per weight
Language model sizeUnknown5.93 GB
Weight formatUnknownTernary g128 with FP16 group scales

ERNIE X1.1 Capabilities

agentschatreasoningsearchtools
Serving providers1
Canonical IDbaidu/ernie-x1.1

Ternary Bonsai 2 27B Capabilities

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

Primary Evidence

Sources and Freshness

Questions

ERNIE X1.1 vs Ternary Bonsai 2 27B FAQs

Is ERNIE X1.1 or Ternary Bonsai 2 27B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE X1.1 and Ternary Bonsai 2 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, ERNIE X1.1 or Ternary Bonsai 2 27B?+

ERNIE X1.1 is $1.00 and Ternary Bonsai 2 27B is $0.075 per million tokens, so Ternary Bonsai 2 27B is cheaper on this metric. ERNIE X1.1 is $4.00 and Ternary Bonsai 2 27B is $0.50 per million tokens, so Ternary Bonsai 2 27B is cheaper on this metric.

Which has a larger context window, ERNIE X1.1 or Ternary Bonsai 2 27B?+

Ternary Bonsai 2 27B has the larger sourced context window. ERNIE X1.1 supports 66K and Ternary Bonsai 2 27B supports 262K.

Which performs better in benchmarks, ERNIE X1.1 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 ERNIE X1.1 or Ternary Bonsai 2 27B be self-hosted?+

Ternary Bonsai 2 27B is the only model in this pair currently marked as self-hostable. ERNIE X1.1 is not marked open weight; Ternary Bonsai 2 27B is open weight.

Can ERNIE X1.1 and Ternary Bonsai 2 27B understand images?+

ERNIE X1.1 is not 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, ERNIE X1.1 or Ternary Bonsai 2 27B?+

Neither has a larger sourced maximum output. ERNIE X1.1 is 66K and Ternary Bonsai 2 27B is —.

Do ERNIE X1.1 and Ternary Bonsai 2 27B support reasoning and tool use?+

ERNIE X1.1: reasoning and tool calling. Ternary Bonsai 2 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, ERNIE X1.1 or Ternary Bonsai 2 27B?+

ERNIE X1.1 has 1 sourced provider route; Ternary Bonsai 2 27B has 1, a tie.

Which offers better value, ERNIE X1.1 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.

Send Feedback