GPT-5.1 vs Ternary Bonsai 8B

At a Glance

Compare
GPT-5.1OpenAI
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#37 of 4625.7 score · 2/3 sources · provisional · missing LiveBench · full-core range 17.1–50.5UnrankedNot in the 46-model eligible cohort
Pricing and Limits
Input priceFrom · USD / 1M tokens$1.25Openai · Sep 3, 2026Not reported
Output priceFrom · USD / 1M tokens$10.00Openai · Sep 3, 2026Not reported
Context windowMaximum documented tokens400K66K
Model facts checkedSep 3, 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

FieldGPT-5.1Ternary Bonsai 8B
DeveloperOpenAIPrismML
FamilyGpt 5 1Bonsai 8b
ModelGPT-5.1Ternary Bonsai 8B
VersionGPT-5.1Ternary Bonsai 8B
Lifecycleactiveactive
Released2025-11-132026-04-18
Knowledge cutoff2024-09-30Unknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window400K66K
Total parametersUnknown8.2B
Active parametersUnknownUnknown
LicenseUnknownapache-2.0
Open weightsNoYes
API availableYesNo
Self-hostableNoYes
Provider accessOpenai (Standard), Openrouter (Standard)Unknown
Capabilitieschat, generation, reasoning, structured_outputs, toolschat, generation
Effective bit widthUnknown1.58 bits per weight
Weight sizeUnknown2.18 GB
Weight formatUnknownTernary Q2_0

GPT-5.1 Capabilities

chatgenerationreasoningstructured outputstools
Serving providers2
Canonical IDopenai/gpt-5.1

Ternary Bonsai 8B Capabilities

chatgeneration
Serving providers0
Canonical IDprism-ml/Ternary-Bonsai-8B

Primary Evidence

Sources and Freshness

Questions

GPT-5.1 vs Ternary Bonsai 8B FAQs

Is GPT-5.1 or Ternary Bonsai 8B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5.1 and Ternary Bonsai 8B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, GPT-5.1 or Ternary Bonsai 8B?+

Only GPT-5.1 has a directly sourced input price: $1.25 per million tokens. Only GPT-5.1 has a directly sourced output price: $10.00 per million tokens.

Which has a larger context window, GPT-5.1 or Ternary Bonsai 8B?+

GPT-5.1 has the larger sourced context window. GPT-5.1 supports 400K and Ternary Bonsai 8B supports 66K.

Which performs better in benchmarks, GPT-5.1 or Ternary Bonsai 8B?+

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

Can GPT-5.1 or Ternary Bonsai 8B be self-hosted?+

Ternary Bonsai 8B is the only model in this pair currently marked as self-hostable. GPT-5.1 is not marked open weight; Ternary Bonsai 8B is open weight.

Can GPT-5.1 and Ternary Bonsai 8B understand images?+

GPT-5.1 is documented with image input; Ternary Bonsai 8B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, GPT-5.1 or Ternary Bonsai 8B?+

Neither has a larger sourced maximum output. GPT-5.1 is 128K and Ternary Bonsai 8B is —.

Do GPT-5.1 and Ternary Bonsai 8B support reasoning and tool use?+

GPT-5.1: reasoning, tool calling, and image input. Ternary Bonsai 8B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, GPT-5.1 or Ternary Bonsai 8B?+

GPT-5.1 has 2 sourced provider routes; Ternary Bonsai 8B has 0, so GPT-5.1 has broader tracked availability.

Which offers better value, GPT-5.1 or Ternary Bonsai 8B?+

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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