| Signal | GPT-4 Turbo Preview | Delta | Llama 3.3 70B Instruct (free) |
|---|---|---|---|
Capabilities | 50 | +17 | |
Pricing | 30 | -- | |
Context window size | 81 | -- | |
Recency | 0 | -48 | |
Output Capacity | 60 | -25 | |
| Overall Result | 1 wins | of 5 | 2 wins |
0
days ranked higher
1
days
29
days ranked higher
OpenAI
Meta
Llama 3.3 70B Instruct (free) saves you $2500.00/month
That's $30000.00/year compared to GPT-4 Turbo Preview at your current usage level of 100K calls/month.
| Metric | GPT-4 Turbo Preview | Llama 3.3 70B Instruct (free) | Winner |
|---|---|---|---|
| Overall Score | 48 | 54 | Llama 3.3 70B Instruct (free) |
| Rank | #255 | #238 | Llama 3.3 70B Instruct (free) |
| Quality Rank | #255 | #238 | Llama 3.3 70B Instruct (free) |
| Adoption Rank | #255 | #238 | Llama 3.3 70B Instruct (free) |
| Parameters | -- | 70B | -- |
| Context Window | 128K | 128K | -- |
| Pricing | $10.00/$30.00/M | Free | -- |
| Signal Scores | |||
| Capabilities | 50 | 33 | GPT-4 Turbo Preview |
| Pricing | 30 | 30 | GPT-4 Turbo Preview |
| Context window size | 81 | 81 | GPT-4 Turbo Preview |
| Recency | 0 | 48 | Llama 3.3 70B Instruct (free) |
| Output Capacity | 60 | 85 | Llama 3.3 70B Instruct (free) |
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 48/100 (rank #255), placing it in the top 12% of all 290 models tracked.
Scores 54/100 (rank #238), placing it in the top 18% of all 290 models tracked.
Llama 3.3 70B Instruct (free) has a 6-point advantage, which typically translates to noticeably better 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
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 3.3 70B Instruct (free) 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 ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (54/100) correlates with better nuance, coherence, and style in long-form content
Llama 3.3 70B Instruct (free) has a moderate advantage with a 5.899999999999999-point lead in composite score. It wins on more signal dimensions, but GPT-4 Turbo Preview has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-4 Turbo Preview
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.3 70B Instruct (free)
100% lower pricing; better value at scale
Best for Reliability
GPT-4 Turbo Preview
Higher uptime and faster response speeds
Best for Prototyping
GPT-4 Turbo Preview
Stronger community support and better developer experience
Best for Production
GPT-4 Turbo Preview
Wider enterprise adoption and proven at scale
by OpenAI
by Meta
| Capability | GPT-4 Turbo Preview | Llama 3.3 70B Instruct (free) |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Meta
Llama 3.3 70B Instruct (free) saves you $54.00/month
That's 100% cheaper than GPT-4 Turbo Preview 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 Turbo Preview | Llama 3.3 70B Instruct (free) |
|---|---|---|
| Context Window | 128K | 128K |
| Max Output Tokens | 4,096 | 128,000 |
| Open Source | Yes | Yes |
| Created | Jan 25, 2024 | Dec 6, 2024 |
Llama 3.3 70B Instruct (free) scores 54/100 (rank #238) compared to GPT-4 Turbo Preview's 48/100 (rank #255), giving it a 6-point advantage. Llama 3.3 70B Instruct (free) is the stronger overall choice, though GPT-4 Turbo Preview may excel in specific areas like certain benchmarks.
GPT-4 Turbo Preview is ranked #255 and Llama 3.3 70B Instruct (free) is ranked #238 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 3.3 70B Instruct (free) is cheaper at $0.00/M output tokens vs GPT-4 Turbo Preview's $30.00/M output tokens — 30000.0x more expensive. Input token pricing: GPT-4 Turbo Preview at $10.00/M vs Llama 3.3 70B Instruct (free) at $0.00/M.
GPT-4 Turbo Preview has a larger context window of 128,000 tokens compared to Llama 3.3 70B Instruct (free)'s 128,000 tokens. A larger context window means the model can process longer documents and conversations.