| Signal | GPT-3.5 Turbo 16k | Delta | Phi 4 |
|---|---|---|---|
Capabilities | 50 | +17 | |
Pricing | 4 | +4 | |
Context window size | 67 | -- | |
Recency | 0 | -55 | |
Output Capacity | 60 | -10 | |
Benchmarks | 0 | -32 | |
| Overall Result | 2 wins | of 6 | 3 wins |
5
days ranked higher
3
days
22
days ranked higher
OpenAI
Microsoft
Phi 4 saves you $487.00/month
That's $5844.00/year compared to GPT-3.5 Turbo 16k at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo 16k | Phi 4 | Winner |
|---|---|---|---|
| Overall Score | 45 | 46 | Phi 4 |
| Rank | #262 | #261 | Phi 4 |
| Quality Rank | #262 | #261 | Phi 4 |
| Adoption Rank | #262 | #261 | Phi 4 |
| Parameters | -- | -- | -- |
| Context Window | 16K | 16K | GPT-3.5 Turbo 16k |
| Pricing | $3.00/$4.00/M | $0.06/$0.14/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 33 | GPT-3.5 Turbo 16k |
| Pricing | 4 | 0 | GPT-3.5 Turbo 16k |
| Context window size | 67 | 67 | GPT-3.5 Turbo 16k |
| Recency | 0 | 55 | Phi 4 |
| Output Capacity | 60 | 70 | Phi 4 |
| Benchmarks | -- | 32 | Phi 4 |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 45/100 (rank #262), placing it in the top 10% of all 290 models tracked.
Scores 46/100 (rank #261), placing it in the top 10% 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 97% better value per quality point. At 1M tokens/day, you'd spend $3.00/month with Phi 4 vs $105.00/month with GPT-3.5 Turbo 16k — a $102.00 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 (16K 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 (46/100) correlates with better nuance, coherence, and style in long-form content
GPT-3.5 Turbo 16k and Phi 4 are extremely close in overall performance (only 1 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-3.5 Turbo 16k
Marginally better benchmark scores; both are excellent
Best for Cost
Phi 4
97% lower pricing; better value at scale
Best for Reliability
GPT-3.5 Turbo 16k
Higher uptime and faster response speeds
Best for Prototyping
GPT-3.5 Turbo 16k
Stronger community support and better developer experience
Best for Production
GPT-3.5 Turbo 16k
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-3.5 Turbo 16k | Phi 4 |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Microsoft
Phi 4 saves you $9.92/month
That's 97% cheaper than GPT-3.5 Turbo 16k 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-3.5 Turbo 16k | Phi 4 |
|---|---|---|
| Context Window | 16K | 16K |
| Max Output Tokens | 4,096 | 16,384 |
| Open Source | Yes | Yes |
| Created | Aug 28, 2023 | Jan 10, 2025 |
Phi 4 scores 46/100 (rank #261) compared to GPT-3.5 Turbo 16k's 45/100 (rank #262), giving it a 1-point advantage. Phi 4 is the stronger overall choice, though GPT-3.5 Turbo 16k may excel in specific areas like certain benchmarks.
GPT-3.5 Turbo 16k is ranked #262 and Phi 4 is ranked #261 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Phi 4 is cheaper at $0.14/M output tokens vs GPT-3.5 Turbo 16k's $4.00/M output tokens — 28.6x more expensive. Input token pricing: GPT-3.5 Turbo 16k at $3.00/M vs Phi 4 at $0.06/M.
GPT-3.5 Turbo 16k has a larger context window of 16,385 tokens compared to Phi 4's 16,384 tokens. A larger context window means the model can process longer documents and conversations.