AI Models · Paid vs Paid

GPT-4 Turbo (batch) Paid vs Muse Spark 1.2 Contributor Paid

GPT-4 Turbo (batch) vs Muse Spark 1.2 Contributor compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

GPT-4 Turbo (batch)PaidOpenAI
$5 /M input
$15 /M outputManaged API (no infra to run)
TypeProprietary
Context window128K tokens
MultimodalYes
Self-hostNo
Muse Spark 1.2 ContributorPaidMeta
$0.1 /M input
$0.2 /M outputManaged API (no infra to run)
TypeProprietary
Context window1M tokens
MultimodalYes
Self-hostNo
Choose Muse Spark 1.2 Contributor for the lower output price ($0.2/M vs $15/M). It also gives you the larger 1M context window.

GPT-4 Turbo (batch) vs Muse Spark 1.2 Contributor specs

SpecGPT-4 Turbo (batch)Muse Spark 1.2 ContributorWinner
MakerOpenAIMeta
TypeProprietaryProprietary
Context window128K tokens1M tokensMuse Spark 1.2 Contributor
Input price$5/M$0.1/MMuse Spark 1.2 Contributor
Output price$15/M$0.2/MMuse Spark 1.2 Contributor
Vision / multimodalYesYes= Tie
Tool / function callingYesYes= Tie
Self-hostableNo (API only)No (API only)
LicenseProprietaryProprietary

Price gap & when to choose each

75×cheaper per output token

Muse Spark 1.2 Contributor is ~75× cheaper than GPT-4 Turbo (batch) on output tokens ($0.2 vs $15 per M tokens).

Choose GPT-4 Turbo (batch) if…
  • You want frontier performance through a managed API
  • You value reliability & ecosystem
  • You don't want to manage infrastructure
Choose Muse Spark 1.2 Contributor if…
  • You want frontier performance through a managed API
  • You need the longer 1M context window
  • You want the lower output price
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityGPT-4 Turbo (batch)Muse Spark 1.2 Contributor
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: GPT-4 Turbo (batch) vs Muse Spark 1.2 Contributor

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

GPT-4 Turbo (batch)
Muse Spark 1.2 Contributor
Intelligence index
7
Coding index
21.5
MMLU-Pro
69.4%
Humanity's Last Exam
3.1%
LiveCodeBench
29.1%
MATH-500
73.7%
AIME
15%
Speed
0 tok/s
Latency
0s
Intelligence per $
0.5

Benchmark data by Artificial Analysis.

How GPT-4 Turbo (batch) and Muse Spark 1.2 Contributor score

🏆 Best value & openness: Muse Spark 1.2 Contributor (3.5 vs 2.8 / 5)
CriterionGPT-4 Turbo (batch)Muse Spark 1.2 Contributor
Cost-efficiency3.05.0
Context window3.55.0
Openness1.51.5
Self-hosting1.01.0
Multimodality5.05.0

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

GPT-4 Turbo (batch) Paid

OpenAI · Proprietary

The latest GPT-4 Turbo model with vision capabilities. Vision requests can now use JSON mode and function calling. Training data: up to December 2023.

Muse Spark 1.2 Contributor Paid

Meta · Proprietary

Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost. It’s meaningfully cheaper than Muse Spark...

Frequently asked questions

GPT-4 Turbo (batch) vs Muse Spark 1.2 Contributor — which is cheaper?

Muse Spark 1.2 Contributor is cheaper on output ($0.2/M vs $15/M).

Which has the larger context window?

Muse Spark 1.2 Contributor offers the larger context window (1M tokens).

GPT-4 Turbo (batch) vs Muse Spark 1.2 Contributor — which should I pick in 2026?

Choose Muse Spark 1.2 Contributor for the lower output price ($0.2/M vs $15/M). It also gives you the larger 1M context window.

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