| Signal | GPT-3.5 Turbo 16k | Delta | GPT-4 Turbo (older v1106) |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 4 | -26 | |
Context window size | 67 | -14 | |
Recency | 0 | -- | |
Output Capacity | 60 | -- | |
| Overall Result | 0 wins | of 5 | 2 wins |
7
days higher
4
days
19
days higher
OpenAI
OpenAI
GPT-3.5 Turbo 16k saves you $2000.00/month
That's $24000.00/year compared to GPT-4 Turbo (older v1106) at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo 16k | GPT-4 Turbo (older v1106) | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #297 | #296 | GPT-4 Turbo (older v1106) |
| Quality Rank | #297 | #296 | GPT-4 Turbo (older v1106) |
| Adoption Rank | #297 | #296 | GPT-4 Turbo (older v1106) |
| Parameters | -- | -- | -- |
| Context Window | 16K | 128K | GPT-4 Turbo (older v1106) |
| Pricing | $3.00/$4.00/M | $10.00/$30.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | GPT-3.5 Turbo 16k |
| Pricing | 4 | 30 | GPT-4 Turbo (older v1106) |
| Context window size | 67 | 81 | GPT-4 Turbo (older v1106) |
| Recency | 0 | 0 | GPT-3.5 Turbo 16k |
| Output Capacity | 60 | 60 | GPT-3.5 Turbo 16k |
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 40/100 (rank #297), placing it in the top -2% of all 290 models tracked.
Scores 40/100 (rank #296), placing it in the top -2% of all 290 models tracked.
With only a 0-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.
GPT-3.5 Turbo 16k offers 83% better value per quality point. At 1M tokens/day, you'd spend $105.00/month with GPT-3.5 Turbo 16k vs $600.00/month with GPT-4 Turbo (older v1106) - a $495.00 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. GPT-3.5 Turbo 16k also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($4.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content
GPT-3.5 Turbo 16k and GPT-4 Turbo (older v1106) are extremely close in overall performance (only 0 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
GPT-3.5 Turbo 16k
83% 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 | GPT-4 Turbo (older v1106) |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
OpenAI
GPT-3.5 Turbo 16k saves you $43.80/month
That's 81% cheaper than GPT-4 Turbo (older v1106) 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 | GPT-4 Turbo (older v1106) |
|---|---|---|
| Context Window | 16K | 128K |
| Max Output Tokens | 4,096 | 4,096 |
| Open Source | No | No |
| Created | Aug 28, 2023 | Nov 6, 2023 |
Both GPT-3.5 Turbo 16k and GPT-4 Turbo (older v1106) score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
GPT-3.5 Turbo 16k is ranked #297 and GPT-4 Turbo (older v1106) is ranked #296 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.
GPT-3.5 Turbo 16k is cheaper at $4.00/M output tokens vs GPT-4 Turbo (older v1106)'s $30.00/M output tokens - 7.5x more expensive. Input token pricing: GPT-3.5 Turbo 16k at $3.00/M vs GPT-4 Turbo (older v1106) at $10.00/M.
GPT-4 Turbo (older v1106) has a larger context window of 128,000 tokens compared to GPT-3.5 Turbo 16k's 16,385 tokens. A larger context window means the model can process longer documents and conversations.