| Signal | GPT-3.5 Turbo | Delta | Llama 3 70B Instruct |
|---|---|---|---|
Capabilities | 50 | +17 | |
Pricing | 2 | +1 | |
Context window size | 67 | +5 | |
Recency | 0 | -5 | |
Output Capacity | 60 | -5 | |
Benchmarks | 0 | -50 | |
| Overall Result | 3 wins | of 6 | 3 wins |
8
days ranked higher
1
days
21
days ranked higher
OpenAI
Meta
Llama 3 70B Instruct saves you $37.00/month
That's $444.00/year compared to GPT-3.5 Turbo at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo | Llama 3 70B Instruct | Winner |
|---|---|---|---|
| Overall Score | 40 | 41 | Llama 3 70B Instruct |
| Rank | #284 | #282 | Llama 3 70B Instruct |
| Quality Rank | #284 | #282 | Llama 3 70B Instruct |
| Adoption Rank | #284 | #282 | Llama 3 70B Instruct |
| Parameters | -- | 70B | -- |
| Context Window | 16K | 8K | GPT-3.5 Turbo |
| Pricing | $0.50/$1.50/M | $0.51/$0.74/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 33 | GPT-3.5 Turbo |
| Pricing | 2 | 1 | GPT-3.5 Turbo |
| Context window size | 67 | 62 | GPT-3.5 Turbo |
| Recency | 0 | 5 | Llama 3 70B Instruct |
| Output Capacity | 60 | 65 | Llama 3 70B Instruct |
| Benchmarks | -- | 50 | Llama 3 70B Instruct |
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 40/100 (rank #284), placing it in the top 2% of all 290 models tracked.
Scores 41/100 (rank #282), placing it in the top 3% 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.
Llama 3 70B Instruct offers 38% better value per quality point. At 1M tokens/day, you'd spend $18.75/month with Llama 3 70B Instruct vs $30.00/month with GPT-3.5 Turbo - a $11.25 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. Llama 3 70B Instruct 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 ($0.74/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (41/100) correlates with better nuance, coherence, and style in long-form content
GPT-3.5 Turbo and Llama 3 70B Instruct are extremely close in overall performance (only 0.6000000000000014 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-3.5 Turbo
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3 70B Instruct
38% lower pricing; better value at scale
Best for Reliability
GPT-3.5 Turbo
Higher uptime and faster response speeds
Best for Prototyping
GPT-3.5 Turbo
Stronger community support and better developer experience
Best for Production
GPT-3.5 Turbo
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-3.5 Turbo | Llama 3 70B Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Meta
Llama 3 70B Instruct saves you $0.8940/month
That's 33% cheaper than GPT-3.5 Turbo 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 | Llama 3 70B Instruct |
|---|---|---|
| Context Window | 16K | 8K |
| Max Output Tokens | 4,096 | 8,000 |
| Open Source | No | Yes |
| Created | May 28, 2023 | Apr 18, 2024 |
Llama 3 70B Instruct scores 41/100 (rank #282) compared to GPT-3.5 Turbo's 40/100 (rank #284), giving it a 1-point advantage. Llama 3 70B Instruct is the stronger overall choice, though GPT-3.5 Turbo may excel in specific areas like certain benchmarks.
GPT-3.5 Turbo is ranked #284 and Llama 3 70B Instruct is ranked #282 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.
Llama 3 70B Instruct is cheaper at $0.74/M output tokens vs GPT-3.5 Turbo's $1.50/M output tokens - 2.0x more expensive. Input token pricing: GPT-3.5 Turbo at $0.50/M vs Llama 3 70B Instruct at $0.51/M.
GPT-3.5 Turbo has a larger context window of 16,385 tokens compared to Llama 3 70B Instruct's 8,192 tokens. A larger context window means the model can process longer documents and conversations.