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Model Comparison

Schematron V2 Small vs o3 Mini HighWhich Is Better in 2026?

Inference net•OpenAI: o3 Mini High logoOpenAI

Schematron V2 Small vs o3 Mini High: which should you choose in 2026?

Schematron V2 Small (by Inference net) and o3 Mini High (by OpenAI) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Schematron V2 Small is about 20.3× cheaper on a blended 3:1 input/output basis ($0.095 vs $1.93 per 1M tokens).

o3 Mini High has the larger context window (200,000 tokens vs 128,000 tokens).

Choose Schematron V2 Small if…

  • • lower blended API cost matters for your workload

Choose o3 Mini High if…

  • • you work with longer documents, transcripts, or codebases
  • • you need a model with explicit reasoning support

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

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Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

Schematron V2 Small and o3 Mini High benchmark results
BenchmarkSchematron V2 Smallo3 Mini High
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

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BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

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OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

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SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

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Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

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AutoBench

A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench.

Weighted peer-assessment score

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GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

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Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

——
Arena preference scores
Arena (Text)

Human preference score

—
1363 ±5

Benchmark sources

Reviewed evidence last updated 2026-08-09. Arena data last refreshed Sep 14, 2026.

Pricing, capabilities, and model facts

Schematron V2 Small and o3 Mini High model facts
FeatureSchematron V2 Smallo3 Mini High
Context & model facts
DeveloperInference netOpenAI
API providerInference.netOpenAI
Input context128,000 tokens200,000 tokens
Maximum output4,096 tokens100,000 tokens
Released——
Added to WritingmateSep 12, 2026Feb 12, 2025
LicenseNot availableNot available
Knowledge cutoff—2023-10-31
Capabilities
InputsTextText, File
OutputsTextText
Provider endpoint accepts tool parametersNoYes
ReasoningNoYes
VisionNoNo
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$0.05$1.10
Output (per 1M tokens)$0.23$4.40
Blended 3:1 input/output$0.095$1.93
API performance
p95 latencyNot measuredNot measured
Output throughputNot measuredNot measured
Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

Data sources

  • Writingmate model catalog (pricing, limits, and availability)

Catalog data last updated Sep 12, 2026.

Why Pay for Multiple Subscriptions?

Comparing Schematron V2 Small from Inference net with o3 Mini High from OpenAI? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for Schematron V2 Small and o3 Mini High
PlanPriceSchematron V2 Smallo3 Mini HighAI ImagesAI Video
Writingmate Pro
Most popular
$20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
Writingmate Ultimate
Power users
$60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
View Plans & Pricing

Schematron V2 Small vs o3 Mini High FAQ

Which is better, Schematron V2 Small or o3 Mini High?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Schematron V2 Small is about 20.3× cheaper on a blended 3:1 input/output basis ($0.095 vs $1.93 per 1M tokens). o3 Mini High has the larger context window (200,000 tokens vs 128,000 tokens).

Which model is cheaper to use through an API?

Schematron V2 Small is about 20.3× cheaper on a blended 3:1 input/output basis ($0.095 vs $1.93 per 1M tokens).

Which model supports more context?

o3 Mini High has the larger context window (200,000 tokens vs 128,000 tokens).

Can I switch between Schematron V2 Small and o3 Mini High?

Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.