API cost decision in 10 seconds

NewSchematron V2 Turbo vs NewFugu Max

Pick Schematron V2 Turbo for lower cost; pick Fugu Max only if the larger context window matters more.

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

Budget verdict

Pick Schematron V2 Turbo for lower cost; pick Fugu Max only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $5 for Fugu Max, saving $4.89 (97.9% lower).

Cost-first pickSchematron V2 Turbo
Context-first pickFugu Max
Sample savings$4.8997.9%
10x traffic gap$48.95

Fugu Max has more context, but Schematron V2 Turbo saves $4.89 on the standard workload. At 10x that traffic, the same price gap is about $48.95. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Schematron V2 Turbo stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickSchematron V2 TurboFugu Max
Input-heavy / RAG5M input + 500K outputSchematron V2 Turbo$0.22$13
Balanced workload1M input + 1M outputSchematron V2 Turbo$0.18$8
Output-heavy chatbot1M input + 5M outputSchematron V2 Turbo$0.78$32
Cheaper input Schematron V2 Turbo $0.03 vs $2 / 1M

Schematron V2 Turbo is $1.97 cheaper per 1M input tokens (98.5% lower; 66.7x difference).

Cheaper output Schematron V2 Turbo $0.15 vs $6 / 1M

Schematron V2 Turbo is $5.85 cheaper per 1M output tokens (97.5% lower; 40x difference).

Larger context Fugu Max 128K vs 1M

Fugu Max has 872K more context (7.81x larger).

Sample workload Schematron V2 Turbo $0.1 vs $5

Schematron V2 Turbo is $4.89 cheaper on the standard workload (97.9% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Schematron V2 Turbo Calculating… Estimated API cost
Fugu Max 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

Schematron V2 Turbo has the lower input price; Schematron V2 Turbo has the lower output price; Fugu Max offers the larger context window. For the 1M input plus 500K output sample, Schematron V2 Turbo is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.1 for Schematron V2 Turbo and $5 for Fugu Max.

Best Fit

Choose Schematron V2 Turbo when you care most about lower input-token price, and lower output-token price.

Choose Fugu Max when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $5 for Fugu Max, saving $4.89 (97.9% lower).
  • Schematron V2 Turbo is $4.89 cheaper on the standard workload (97.9% lower).
  • Schematron V2 Turbo is $1.97 cheaper per 1M input tokens (98.5% lower; 66.7x difference).
  • Schematron V2 Turbo is $5.85 cheaper per 1M output tokens (97.5% lower; 40x difference).
  • Fugu Max has 872K more context (7.81x larger).
Head-to-Head Specs
FeatureNewSchematron V2 Turbo
(Inference.net)
NewFugu Max
(Sakana)
Input Price
prompt tokens per 1M
$0.03$2
Completion Price
per 1M tokens
$0.15$6
Sample Workload Cost
1M input + 500K output
$0.1$5
Context Window128K1M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionSchematron V2 TurboOn the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $5 for Fugu Max, saving $4.89 (97.9% lower).
High-volume input processingSchematron V2 TurboLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsSchematron V2 TurboLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workFugu MaxA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • Sakana Namazu can replace Fugu Max when lower sample workload cost matters most: $2.95.

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

Inference.net catalog

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

Open Inference.net models

Sakana catalog

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

Open Sakana models
Schematron V2 Turbo

Schematron V2 Turbo is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes throughput for high-volume extraction workloads. Extraction instructions must be supplied through a JSON schema in response_format rather...

Fugu Max

Fugu Max is the cost-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to route...