API cost decision in 10 seconds

NewBeam 1.0 501B A23B vs Schematron V2 Turbo

Pick Schematron V2 Turbo for lower cost; pick Beam 1.0 501B A23B 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 Beam 1.0 501B A23B 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 $0.75 for Beam 1.0 501B A23B, saving $0.65 (86% lower).

Cost-first pickSchematron V2 Turbo
Context-first pickBeam 1.0 501B A23B
Sample savings$0.6586%
10x traffic gap$6.45

Beam 1.0 501B A23B has more context, but Schematron V2 Turbo saves $0.65 on the standard workload. At 10x that traffic, the same price gap is about $6.45. 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 pickBeam 1.0 501B A23BSchematron V2 Turbo
Input-heavy / RAG5M input + 500K outputSchematron V2 Turbo$1.75$0.22
Balanced workload1M input + 1M outputSchematron V2 Turbo$1.25$0.18
Output-heavy chatbot1M input + 5M outputSchematron V2 Turbo$5.25$0.78
Cheaper input Schematron V2 Turbo $0.25 vs $0.03 / 1M

Schematron V2 Turbo is $0.22 cheaper per 1M input tokens (88% lower; 8.33x difference).

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

Schematron V2 Turbo is $0.85 cheaper per 1M output tokens (85% lower; 6.67x difference).

Larger context Beam 1.0 501B A23B 1.05M vs 128K

Beam 1.0 501B A23B has 920.58K more context (8.19x larger).

Sample workload Schematron V2 Turbo $0.75 vs $0.1

Schematron V2 Turbo is $0.65 cheaper on the standard workload (86% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Beam 1.0 501B A23B Calculating… Estimated API cost
Schematron V2 Turbo 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; Beam 1.0 501B A23B 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 $0.75 for Beam 1.0 501B A23B and $0.1 for Schematron V2 Turbo.

Best Fit

Choose Beam 1.0 501B A23B when you care most about larger context window.

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

Decision Notes
  • On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $0.75 for Beam 1.0 501B A23B, saving $0.65 (86% lower).
  • Schematron V2 Turbo is $0.65 cheaper on the standard workload (86% lower).
  • Schematron V2 Turbo is $0.22 cheaper per 1M input tokens (88% lower; 8.33x difference).
  • Schematron V2 Turbo is $0.85 cheaper per 1M output tokens (85% lower; 6.67x difference).
  • Beam 1.0 501B A23B has 920.58K more context (8.19x larger).
Head-to-Head Specs
FeatureNewBeam 1.0 501B A23B
(Reflection)		Schematron V2 Turbo
(Inference.net)
Input Price
prompt tokens per 1M		$0.25$0.03
Completion Price
per 1M tokens		$1$0.15
Sample Workload Cost
1M input + 500K output		$0.75$0.1
Context Window1.05M128K
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 $0.75 for Beam 1.0 501B A23B, saving $0.65 (86% 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 workBeam 1.0 501B A23BA 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.
Larger context near this budget
  • Llama 4 Scout offers 1.31M context with $0.25 sample workload cost.
  • MiMo-V2.6-Flash offers 1.05M context with $0.28 sample workload cost.
  • GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
  • GPT-6 Luna Pro offers 1.05M context with $0.35 sample workload cost.

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

Reflection catalog

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

Open Reflection models

Inference.net catalog

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

Open Inference.net models
Beam 1.0 501B A23B

Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active parameters per token, and a...

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...