| Signal | GPT-5.4 Nano | Delta | autofixer-01 |
|---|---|---|---|
Capabilities | 100 | +83 | |
Benchmarks | 90 | +90 | |
Pricing | 99 | -1 | |
Context window size | 89 | +89 | |
Recency | 100 | +8 | |
Output Capacity | 85 | +65 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
79.3
current score
GPT-5.4 Nano
right now
31.9
current score
OpenAI
Vercel
autofixer-01 saves you $82.50/month
That's $990.00/year compared to GPT-5.4 Nano at your current usage level of 100K calls/month.
| Metric | GPT-5.4 Nano | autofixer-01 | Winner |
|---|---|---|---|
| Overall Score | 79 | 32 | GPT-5.4 Nano |
| Rank | #42 | #334 | GPT-5.4 Nano |
| Quality Rank | #42 | #334 | GPT-5.4 Nano |
| Adoption Rank | #42 | #334 | GPT-5.4 Nano |
| Parameters | -- | -- | -- |
| Context Window | 400K | -- | -- |
| Pricing | $0.20/$1.25/M | Free | -- |
| Signal Scores | |||
| Capabilities | 100 | 17 | GPT-5.4 Nano |
| Benchmarks | 90 | -- | GPT-5.4 Nano |
| Pricing | 99 | 100 | autofixer-01 |
| Context window size | 89 | 0 | GPT-5.4 Nano |
| Recency | 100 | 93 | GPT-5.4 Nano |
| Output Capacity | 85 | 20 | GPT-5.4 Nano |
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.
Scores 79/100 (rank #42), placing it in the top 86% of all 290 models tracked.
Scores 32/100 (rank #334), placing it in the top -15% of all 290 models tracked.
GPT-5.4 Nano has a 47-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. autofixer-01 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (79/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-5.4 Nano clearly outperforms autofixer-01 with a significant 47.4-point lead. For most general use cases, GPT-5.4 Nano is the stronger choice. However, autofixer-01 may still excel in niche scenarios.
Best for Quality
GPT-5.4 Nano
Marginally better benchmark scores; both are excellent
Best for Cost
autofixer-01
100% lower pricing; better value at scale
Best for Reliability
GPT-5.4 Nano
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.4 Nano
Stronger community support and better developer experience
Best for Production
GPT-5.4 Nano
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.4 Nano | autofixer-01 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Vercel
autofixer-01 saves you $1.86/month
That's 100% cheaper than GPT-5.4 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.
| Parameter | GPT-5.4 Nano | autofixer-01 |
|---|---|---|
| Context Window | 400K | -- |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | No |
| Created | Mar 17, 2026 | Oct 1, 2025 |