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GPT-4.1 Nano vs autofixer-01

GPT-4.1 Nano

OpenAI

29#428
vs
autofixer-01

Vercel

24#430
Signal-by-Signal Comparison
SignalGPT-4.1 NanoDeltaautofixer-01
Capabilities
83
+67
17
Benchmarks
23
+23
0
Pricing
100
0
100
Context window size
96
+96
0
Recency
31
-31
61
Output Capacity
96
+76
20
Overall Result
4 wins
of 6
2 wins
GPT-4.1 Nano wins 4 of 6 signals

Score History

Score History (37 data points)
GPT-4.1 Nanoautofixer-01
GPT-4.1 Nano

29.4

current score

Leader

GPT-4.1 Nano

right now

autofixer-01

24.2

current score

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

GPT-4.1 Nano

OpenAI

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

autofixer-01

Vercel

Best Value
Per request$0.000000
Daily$0.00
Monthly$0.00
Annual$0.00

autofixer-01 saves you $30.00/month

That's $360.00/year compared to GPT-4.1 Nano at your current usage level of 100K calls/month.

100% cheaper
Choose autofixer-01 for cost optimization

GPT-4.1 Nano pricing:
Input:$0.10/M tokens
Output:$0.40/M tokens
autofixer-01 pricing:
Input:$0.00/M tokens
Output:$0.00/M tokens
Winner
GPT-4.1 Nano

OpenAI

29

Composite Score

autofixer-01

Vercel

24

Composite Score

Signal-by-Signal Comparison
MetricGPT-4.1 Nanoautofixer-01Winner
Overall Score
29
24
GPT-4.1 Nano
Rank#428#430
GPT-4.1 Nano
Quality Rank#428#430
GPT-4.1 Nano
Adoption Rank#428#430
GPT-4.1 Nano
Parameters------
Context Window1048K----
Pricing$0.10/$0.40/MFree--
Signal Scores
Capabilities
83
17
GPT-4.1 Nano
Benchmarks
23
--
GPT-4.1 Nano
Pricing
100
100
autofixer-01
Context window size
96
0
GPT-4.1 Nano
Recency
31
61
autofixer-01
Output Capacity
96
20
GPT-4.1 Nano
Benchmark Head-to-Head(1 benchmarks)
GPT-4.1 Nano: 0autofixer-01: 0
GPT-4.1 Nano
autofixer-01
Normalized 0-100%
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 NanoLimited

Scores 29/100 (rank #428), placing it in the top -47% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
autofixer-01Limited

Scores 24/100 (rank #430), placing it in the top -48% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

GPT-4.1 Nano has a 5-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.

When to Use Each Model

Choose GPT-4.1 Nano when you need:

  • Processing long documents or large codebases (1048K token context)
  • Multimodal workflows that require image understanding
  • Agentic applications using tool/function calling

Choose autofixer-01 when you need:

  • High-volume production workloads where API costs must be minimized
Cost-Performance Analysis
GPT-4.1 Nano
Input cost$0.10/M tokens
Output cost$0.40/M tokens
Cost per quality point$0.017
Est. monthly (1M tokens/day)$7.50
autofixer-01
Input cost$0.00/M tokens
Output cost$0.00/M tokens
Cost per quality point$0.000
Est. monthly (1M tokens/day)$0.00

Both models are priced similarly, so the decision comes down to quality and features rather than cost.

Latency & Speed
GPT-4.1 NanoFaster
Speed score0/100
autofixer-01
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. autofixer-01 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 ($0.00/M) reduces costs when processing thousands of records daily

autofixer-01

Creative writing & content

Higher overall composite score (29/100) 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 has a moderate advantage with a 5.199999999999999-point lead in composite score. It wins on more signal dimensions, but autofixer-01 has specific strengths that could make it the better choice for certain workflows.

GPT-4.1 Nano
Recommended

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • 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 Vercel

  • Choose for Cost - 100% lower pricing; better value at scale
Capability Comparison
CapabilityGPT-4.1 Nanoautofixer-01
Vision (Image Input)differs
Function Callingdiffers
Streaming
JSON Modediffers
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-4.1 Nano

OpenAI

$0.6600
estimated monthly cost

autofixer-01

Vercel

Best Value
$0.000000
estimated monthly cost

autofixer-01 saves you $0.6600/month

That's 100% cheaper than GPT-4.1 Nano 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 Nanoautofixer-01
Context Window1.0M--
Max Output Tokens942,818--
Open SourceNoNo
CreatedApr 14, 2025Oct 1, 2025
Last updated: 9m ago

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GPT-4.1 Nano vs autofixer-01 (2026) | LM Market Cap