| Signal | GPT-4.1 Nano | Delta | Phi 4 |
|---|---|---|---|
Capabilities | 83 | +50 | |
Benchmarks | 75 | +8 | |
Pricing | 0 | +0 | |
Context window size | 96 | +29 | |
Recency | 69 | +17 | |
Output Capacity | 75 | +5 | |
| Overall Result | 6 wins | of 6 | 0 wins |
11
days higher
7
days
12
days higher
OpenAI
Microsoft
Phi 4 saves you $16.50/month
That's $198.00/year compared to GPT-4.1 Nano at your current usage level of 100K calls/month.
| Metric | GPT-4.1 Nano | Phi 4 | Winner |
|---|---|---|---|
| Overall Score | 66 | 66 | GPT-4.1 Nano |
| Rank | #79 | #81 | GPT-4.1 Nano |
| Quality Rank | #79 | #81 | GPT-4.1 Nano |
| Adoption Rank | #79 | #81 | GPT-4.1 Nano |
| Parameters | -- | -- | -- |
| Context Window | 1048K | 16K | GPT-4.1 Nano |
| Pricing | $0.10/$0.40/M | $0.07/$0.14/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 33 | GPT-4.1 Nano |
| Benchmarks | 75 | 68 | GPT-4.1 Nano |
| Pricing | 0 | 0 | GPT-4.1 Nano |
| Context window size | 96 | 67 | GPT-4.1 Nano |
| Recency | 69 | 51 | GPT-4.1 Nano |
| Output Capacity | 75 | 70 | GPT-4.1 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%). Here's what the scores mean for these two models:
Scores 66/100 (rank #79), placing it in the top 73% of all 290 models tracked.
Scores 66/100 (rank #81), placing it in the top 72% of all 290 models tracked.
With only a 1-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.
Phi 4 offers 59% better value per quality point. At 1M tokens/day, you'd spend $3.08/month with Phi 4 vs $7.50/month with GPT-4.1 Nano - a $4.42 monthly difference.
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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Phi 4 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1048K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.14/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (66/100) 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-4.1 Nano and Phi 4 are extremely close in overall performance (only 0.5999999999999943 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4.1 Nano
Marginally better benchmark scores; both are excellent
Best for Cost
Phi 4
59% lower pricing; better value at scale
Best for Reliability
GPT-4.1 Nano
Higher uptime and faster response speeds
Best for Prototyping
GPT-4.1 Nano
Stronger community support and better developer experience
Best for Production
GPT-4.1 Nano
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4.1 Nano | Phi 4 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Microsoft
Phi 4 saves you $0.3750/month
That's 57% 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.
| Parameter | GPT-4.1 Nano | Phi 4 |
|---|---|---|
| Context Window | 1.0M | 16K |
| Max Output Tokens | 32,768 | 16,384 |
| Open Source | No | Yes |
| Created | Apr 14, 2025 | Jan 10, 2025 |
GPT-4.1 Nano scores 66/100 (rank #79) compared to Phi 4's 66/100 (rank #81), giving it a 1-point advantage. GPT-4.1 Nano is the stronger overall choice, though Phi 4 may excel in specific areas like cost efficiency.
GPT-4.1 Nano is ranked #79 and Phi 4 is ranked #81 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Phi 4 is cheaper at $0.14/M output tokens vs GPT-4.1 Nano's $0.40/M output tokens - 2.9x more expensive. Input token pricing: GPT-4.1 Nano at $0.10/M vs Phi 4 at $0.07/M.
GPT-4.1 Nano has a larger context window of 1,047,576 tokens compared to Phi 4's 16,384 tokens. A larger context window means the model can process longer documents and conversations.