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GPT-4.1 Nano vs Perceptron Mk1.5

GPT-4.1 Nano

OpenAI

42#235
vs
Perceptron Mk1.5

perceptron

40#237
Signal-by-Signal Comparison
SignalGPT-4.1 NanoDeltaPerceptron Mk1.5
Capabilities
83
--
83
Benchmarks
44
+44
0
Pricing
100
+1
99
Context window size
96
+23
73
Recency
37
-63
100
Output Capacity
72
+10
63
Overall Result
4 wins
of 6
1 wins
GPT-4.1 Nano wins 4 of 6 signals

Score History

Score History (32 data points)
GPT-4.1 NanoPerceptron Mk1.5
GPT-4.1 Nano

42.1

current score

Leader

GPT-4.1 Nano

right now

Perceptron Mk1.5

40

current score

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

GPT-4.1 Nano

OpenAI

Best Value
Per request$0.000300
Daily$1.00
Monthly$30.00
Annual$360.00

Perceptron Mk1.5

perceptron

Per request$0.000900
Daily$3.00
Monthly$90.00
Annual$1080.00

GPT-4.1 Nano saves you $60.00/month

That's $720.00/year compared to Perceptron Mk1.5 at your current usage level of 100K calls/month.

67% cheaper
Choose GPT-4.1 Nano for cost optimization

GPT-4.1 Nano pricing:
Input:$0.10/M tokens
Output:$0.40/M tokens
Perceptron Mk1.5 pricing:
Input:$0.15/M tokens
Output:$1.50/M tokens
Winner
GPT-4.1 Nano

OpenAI

42

Composite Score

Perceptron Mk1.5

perceptron

40

Composite Score

Signal-by-Signal Comparison
MetricGPT-4.1 NanoPerceptron Mk1.5Winner
Overall Score
42
40
GPT-4.1 Nano
Rank#235#237
GPT-4.1 Nano
Quality Rank#235#237
GPT-4.1 Nano
Adoption Rank#235#237
GPT-4.1 Nano
Parameters------
Context Window1048K37K
GPT-4.1 Nano
Pricing$0.10/$0.40/M$0.15/$1.50/M--
Signal Scores
Capabilities
83
83
GPT-4.1 Nano
Benchmarks
44
--
GPT-4.1 Nano
Pricing
100
99
GPT-4.1 Nano
Context window size
96
73
GPT-4.1 Nano
Recency
37
100
Perceptron Mk1.5
Output Capacity
72
63
GPT-4.1 Nano
Benchmark Head-to-Head(2 benchmarks)
GPT-4.1 Nano: 0Perceptron Mk1.5: 0
GPT-4.1 Nano
Perceptron Mk1.5
Normalized 0-100%
Arena Elo
1322-
BigCodeBench
28.4%-
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-4.1 NanoEntry Level

Scores 42/100 (rank #235), placing it in the top 19% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Perceptron Mk1.5Entry Level

Scores 40/100 (rank #237), placing it in the top 19% 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-4.1 Nano when you need:

  • High-volume production workloads where API costs must be minimized
  • Processing long documents or large codebases (1048K token context)

Choose Perceptron Mk1.5 when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
GPT-4.1 NanoBest Value
Input cost$0.10/M tokens
Output cost$0.40/M tokens
Cost per quality point$0.012
Est. monthly (1M tokens/day)$7.50
Perceptron Mk1.5
Input cost$0.15/M tokens
Output cost$1.50/M tokens
Cost per quality point$0.041
Est. monthly (1M tokens/day)$24.75

GPT-4.1 Nano offers 70% better value per quality point. At 1M tokens/day, you'd spend $7.50/month with GPT-4.1 Nano vs $24.75/month with Perceptron Mk1.5 - a $17.25 monthly difference.

Latency & Speed
GPT-4.1 NanoFaster
Speed score0/100
Perceptron Mk1.5
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-4.1 Nano

Customer support chatbot

Suitable for user-facing chat with competitive response times. GPT-4.1 Nano also offers lower per-token costs for high-volume support

GPT-4.1 Nano

Long document analysis

Larger context window (1048K tokens) can process longer documents, contracts, and research papers in a single pass

GPT-4.1 Nano

Batch data extraction

Lower output pricing ($0.40/M) reduces costs when processing thousands of records daily

GPT-4.1 Nano

Creative writing & content

Higher overall composite score (42/100) correlates with better nuance, coherence, and style in long-form content

GPT-4.1 Nano

Image understanding & OCR

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

GPT-4.1 Nano
Which Should You Choose?
Our recommendation:
GPT-4.1 Nano

GPT-4.1 Nano and Perceptron Mk1.5 are extremely close in overall performance (only 2.1000000000000014 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

GPT-4.1 Nano
Recommended

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 70% 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

by perceptron

Consider for specialized use cases.

Capability Comparison
CapabilityGPT-4.1 NanoPerceptron Mk1.5
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoningdiffers
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-4.1 Nano

OpenAI

Best Value
$0.6600
estimated monthly cost

Perceptron Mk1.5

perceptron

$2.07
estimated monthly cost

GPT-4.1 Nano saves you $1.41/month

That's 68% cheaper than Perceptron Mk1.5 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-4.1 NanoPerceptron Mk1.5
Context Window1.0M37K
Max Output Tokens32,7688,192
Open SourceNoNo
CreatedApr 14, 2025Sep 25, 2026
Last updated: 57m ago

相关对比

GPT-4.1 Nano vs Perceptron Mk1.5 (2026) | LM Market Cap