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Model Comparison

Muse Spark 1.2 Contributor vs GPT-4.1Which Is Better in 2026?

Meta: Muse Spark 1.2 Contributor logoMeta•OpenAI: GPT-4.1 logoOpenAI

Muse Spark 1.2 Contributor vs GPT-4.1: which should you choose in 2026?

Muse Spark 1.2 Contributor (by Meta) and GPT-4.1 (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.

Muse Spark 1.2 Contributor is about 28.0× cheaper on a blended 3:1 input/output basis ($0.125 vs $3.50 per 1M tokens).

Choose Muse Spark 1.2 Contributor if…

  • • lower blended API cost matters for your workload
  • • you need a model with explicit reasoning support

Choose GPT-4.1 if…

  • • your own prompt tests favor its output; shared comparable evidence does not identify a unique advantage

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.

Chat with both models
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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.

Muse Spark 1.2 Contributor and GPT-4.1 benchmark results
BenchmarkMuse Spark 1.2 ContributorGPT-4.1
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

—
39.6%
SWE-bench
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

——

Benchmark sources

Reviewed evidence last updated 2026-08-09.

Pricing, capabilities, and model facts

Muse Spark 1.2 Contributor and GPT-4.1 model facts
FeatureMuse Spark 1.2 ContributorGPT-4.1
Context & model facts
DeveloperMetaOpenAI
API providerMetaOpenAI
Input context1,048,576 tokens1,047,576 tokens
Maximum output—32,768 tokens
Released——
Added to WritingmateAug 21, 2026Apr 14, 2025
LicenseNot availableNot available
Knowledge cutoff—2024-06-30
Capabilities
InputsText, Image, Video, File, AudioImage, Text, File
OutputsTextText
Provider endpoint accepts tool parametersYesYes
ReasoningYesNo
VisionYesYes
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$0.10$2.00
Output (per 1M tokens)$0.20$8.00
Blended 3:1 input/output$0.125$3.50
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 Aug 21, 2026.

Why Pay for Multiple Subscriptions?

Comparing Muse Spark 1.2 Contributor from Meta with GPT-4.1 from OpenAI? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for Muse Spark 1.2 Contributor and GPT-4.1
PlanPriceMuse Spark 1.2 ContributorGPT-4.1AI 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

Muse Spark 1.2 Contributor vs GPT-4.1 FAQ

Which is better, Muse Spark 1.2 Contributor or GPT-4.1?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Muse Spark 1.2 Contributor is about 28.0× cheaper on a blended 3:1 input/output basis ($0.125 vs $3.50 per 1M tokens).

Which model is cheaper to use through an API?

Muse Spark 1.2 Contributor is about 28.0× cheaper on a blended 3:1 input/output basis ($0.125 vs $3.50 per 1M tokens).

Which model supports more context?

The published context windows are close enough that this page does not treat the difference as a material advantage.

Can I switch between Muse Spark 1.2 Contributor and GPT-4.1?

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.