API cost decision in 10 seconds

NewPerceptron Mk1.5 vs Ternary Bonsai 2 27B

Pick Ternary Bonsai 2 27B when budget and context both matter.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Ternary Bonsai 2 27B when budget and context both matter.

On the standard 1M input plus 500K output workload, Ternary Bonsai 2 27B is estimated at $0.33 vs $0.9 for Perceptron Mk1.5, saving $0.57 (63.9% lower).

Cost-first pickTernary Bonsai 2 27B
Context-first pickTernary Bonsai 2 27B
Sample savings$0.5763.9%
10x traffic gap$5.75

Ternary Bonsai 2 27B is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $5.75. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Ternary Bonsai 2 27B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickPerceptron Mk1.5Ternary Bonsai 2 27B
Input-heavy / RAG5M input + 500K outputTernary Bonsai 2 27B$1.5$0.62
Balanced workload1M input + 1M outputTernary Bonsai 2 27B$1.65$0.57
Output-heavy chatbot1M input + 5M outputTernary Bonsai 2 27B$7.65$2.58
Cheaper input Ternary Bonsai 2 27B $0.15 vs $0.075 / 1M

Ternary Bonsai 2 27B is $0.07 cheaper per 1M input tokens (50% lower; 2x difference).

Cheaper output Ternary Bonsai 2 27B $1.5 vs $0.5 / 1M

Ternary Bonsai 2 27B is $1 cheaper per 1M output tokens (66.7% lower; 3x difference).

Larger context Ternary Bonsai 2 27B 36.86K vs 262.14K

Ternary Bonsai 2 27B has 225.28K more context (7.11x larger).

Sample workload Ternary Bonsai 2 27B $0.9 vs $0.33

Ternary Bonsai 2 27B is $0.57 cheaper on the standard workload (63.9% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Perceptron Mk1.5 Calculating… Estimated API cost
Ternary Bonsai 2 27B Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Ternary Bonsai 2 27B has the lower input price; Ternary Bonsai 2 27B has the lower output price; Ternary Bonsai 2 27B offers the larger context window. For the 1M input plus 500K output sample, Ternary Bonsai 2 27B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.9 for Perceptron Mk1.5 and $0.33 for Ternary Bonsai 2 27B.

Best Fit

Choose Perceptron Mk1.5 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Ternary Bonsai 2 27B when you care most about lower input-token price, lower output-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Ternary Bonsai 2 27B is estimated at $0.33 vs $0.9 for Perceptron Mk1.5, saving $0.57 (63.9% lower).
  • Ternary Bonsai 2 27B is $0.57 cheaper on the standard workload (63.9% lower).
  • Ternary Bonsai 2 27B is $0.07 cheaper per 1M input tokens (50% lower; 2x difference).
  • Ternary Bonsai 2 27B is $1 cheaper per 1M output tokens (66.7% lower; 3x difference).
  • Ternary Bonsai 2 27B has 225.28K more context (7.11x larger).
Head-to-Head Specs
FeatureNewPerceptron Mk1.5
(Perceptron)
Ternary Bonsai 2 27B
(PrismML)
Input Price
prompt tokens per 1M
$0.15$0.075
Completion Price
per 1M tokens
$1.5$0.5
Sample Workload Cost
1M input + 500K output
$0.9$0.33
Context Window36.86K262.14K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionTernary Bonsai 2 27BOn the standard 1M input plus 500K output workload, Ternary Bonsai 2 27B is estimated at $0.33 vs $0.9 for Perceptron Mk1.5, saving $0.57 (63.9% lower).
High-volume input processingTernary Bonsai 2 27BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsTernary Bonsai 2 27BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workTernary Bonsai 2 27BA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • No lower-cost same-provider swap is currently tracked for this pair.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

Perceptron catalog

Review all tracked Perceptron models before deciding whether this matchup is the right shortlist.

Open Perceptron models

PrismML catalog

Check other PrismML models with comparable pricing, context, or release timing.

Open PrismML models
Perceptron Mk1.5

Perceptron Mk1.5 is Perceptron's embodied reasoning model for physical agents. It accepts text, image, video, and audio input, and answers with text plus optional structured annotations: points, boxes, polygons, tracks,...

Ternary Bonsai 2 27B

Bonsai 2 27B is a 27B-parameter reasoning model from PrismML derived from Qwen3.8-27B. It supports coding, mathematics, tool calling, and image understanding with a 262K-token context window. Ternary compression shrinks...