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GPT-5.4 Nano (batch) vs Muse Spark 1.2

Signal-by-Signal Comparison
SignalGPT-5.4 Nano (batch)DeltaMuse Spark 1.2
Capabilities
100
--
100
Benchmarks
90
+90
0
Pricing
99
+4
96
Context window size
89
-7
96
Recency
100
--
100
Output Capacity
82
-14
96
Overall Result
2 wins
of 6
2 wins
It's a tie - both models win 2 signals each

Score History

Score History (6 data points)
GPT-5.4 Nano (batch)Muse Spark 1.2
GPT-5.4 Nano (batch)

79.3

current score

Leader

Muse Spark 1.2

right now

Muse Spark 1.2

81.1

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

GPT-5.4 Nano (batch)

OpenAI

Best Value
Per request$0.000412
Daily$1.38
Monthly$41.25
Annual$495.00

Muse Spark 1.2

meta

Per request$0.003375
Daily$11.25
Monthly$337.50
Annual$4050.00

GPT-5.4 Nano (batch) saves you $296.25/month

That's $3555.00/year compared to Muse Spark 1.2 at your current usage level of 100K calls/month.

88% cheaper
Choose GPT-5.4 Nano (batch) for cost optimization

GPT-5.4 Nano (batch) pricing:
Input:$0.10/M tokens
Output:$0.63/M tokens
Muse Spark 1.2 pricing:
Input:$1.25/M tokens
Output:$4.25/M tokens
GPT-5.4 Nano (batch)

OpenAI

79

Composite Score

Winner
Muse Spark 1.2

meta

81

Composite Score

Signal-by-Signal Comparison
MetricGPT-5.4 Nano (batch)Muse Spark 1.2Winner
Overall Score
79
81
Muse Spark 1.2
Rank#93#82
Muse Spark 1.2
Quality Rank#93#82
Muse Spark 1.2
Adoption Rank#93#82
Muse Spark 1.2
Parameters------
Context Window400K1049K
Muse Spark 1.2
Pricing$0.10/$0.63/M$1.25/$4.25/M--
Signal Scores
Capabilities
100
100
GPT-5.4 Nano (batch)
Benchmarks
90
--
GPT-5.4 Nano (batch)
Pricing
99
96
GPT-5.4 Nano (batch)
Context window size
89
96
Muse Spark 1.2
Recency
100
100
GPT-5.4 Nano (batch)
Output Capacity
82
96
Muse Spark 1.2
Benchmark Head-to-Head(11 benchmarks)
GPT-5.4 Nano: 0Muse Spark: 0
GPT-5.4 Nano
Muse Spark
Normalized 0-100%
MMLU
94%-
MMLU-Pro
87%-
GPQA Diamond
88.5%-
MATH-500
95.5%-
HumanEval
97.5%-
SWE-bench Verified
80%-
IFEval
93.5%-
BBH
92%-
Arena Elo
1485-
LiveBench
79%-
HLE
39%-
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

GPT-5.4 Nano (batch)Strong Performer

Scores 79/100 (rank #93), placing it in the top 68% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Muse Spark 1.2Strong Performer

Scores 81/100 (rank #82), placing it in the top 72% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 2-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose GPT-5.4 Nano (batch) when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving

Choose Muse Spark 1.2 when you need:

  • Processing long documents or large codebases (1049K token context)
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
GPT-5.4 Nano (batch)Best Value
Input cost$0.10/M tokens
Output cost$0.63/M tokens
Cost per quality point$0.009
Est. monthly (1M tokens/day)$10.88
Muse Spark 1.2
Input cost$1.25/M tokens
Output cost$4.25/M tokens
Cost per quality point$0.068
Est. monthly (1M tokens/day)$82.50

GPT-5.4 Nano (batch) offers 87% better value per quality point. At 1M tokens/day, you'd spend $10.88/month with GPT-5.4 Nano (batch) vs $82.50/month with Muse Spark 1.2 - a $71.63 monthly difference.

Latency & Speed
GPT-5.4 Nano (batch)Faster
Speed score0/100
Muse Spark 1.2
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

GPT-5.4 Nano (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. GPT-5.4 Nano (batch) also offers lower per-token costs for high-volume support

GPT-5.4 Nano (batch)

Long document analysis

Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass

Muse Spark 1.2

Batch data extraction

Lower output pricing ($0.63/M) reduces costs when processing thousands of records daily

GPT-5.4 Nano (batch)

Creative writing & content

Higher overall composite score (81/100) correlates with better nuance, coherence, and style in long-form content

Muse Spark 1.2

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

GPT-5.4 Nano (batch)
Which Should You Choose?
Our recommendation:
Muse Spark 1.2

GPT-5.4 Nano (batch) and Muse Spark 1.2 are extremely close in overall performance (only 1.7999999999999972 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 87% lower pricing; better value at scale
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale
Muse Spark 1.2
Recommended

by meta

Consider for specialized use cases.

Capability Comparison
CapabilityGPT-5.4 Nano (batch)Muse Spark 1.2
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-5.4 Nano (batch)

OpenAI

Best Value
$0.9300
estimated monthly cost

Muse Spark 1.2

meta

$7.35
estimated monthly cost

GPT-5.4 Nano (batch) saves you $6.42/month

That's 87% cheaper than Muse Spark 1.2 at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGPT-5.4 Nano (batch)Muse Spark 1.2
Context Window400K1.0M
Max Output Tokens128,000943,718
Open SourceNoNo
CreatedMar 17, 2026Aug 5, 2026
Last updated: 26m ago

相关对比

GPT-5.4 Nano (batch) vs Muse Spark 1.2 (2026) | LM Market Cap