| Signal | GPT-4 (older v0314) | Delta | Llama 3.1 405B (base) |
|---|---|---|---|
Capabilities | 50 | +33 | |
Pricing | 60 | +56 | |
Context window size | 62 | -10 | |
Recency | 0 | -25 | |
Output Capacity | 60 | -15 | |
| Overall Result | 2 wins | of 5 | 3 wins |
30
days ranked higher
0
days
0
days ranked higher
OpenAI
Meta
Llama 3.1 405B (base) saves you $5400.00/month
That's $64800.00/year compared to GPT-4 (older v0314) at your current usage level of 100K calls/month.
| Metric | GPT-4 (older v0314) | Llama 3.1 405B (base) | Winner |
|---|---|---|---|
| Overall Score | 44 | 38 | GPT-4 (older v0314) |
| Rank | #270 | #283 | GPT-4 (older v0314) |
| Quality Rank | #270 | #283 | GPT-4 (older v0314) |
| Adoption Rank | #270 | #283 | GPT-4 (older v0314) |
| Parameters | -- | 405B | -- |
| Context Window | 8K | 33K | Llama 3.1 405B (base) |
| Pricing | $30.00/$60.00/M | $4.00/$4.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 17 | GPT-4 (older v0314) |
| Pricing | 60 | 4 | GPT-4 (older v0314) |
| Context window size | 62 | 72 | Llama 3.1 405B (base) |
| Recency | 0 | 25 | Llama 3.1 405B (base) |
| Output Capacity | 60 | 75 | Llama 3.1 405B (base) |
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 44/100 (rank #270), placing it in the top 7% of all 290 models tracked.
Scores 38/100 (rank #283), placing it in the top 3% of all 290 models tracked.
GPT-4 (older v0314) has a 6-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Llama 3.1 405B (base) offers 91% better value per quality point. At 1M tokens/day, you'd spend $120.00/month with Llama 3.1 405B (base) vs $1350.00/month with GPT-4 (older v0314) — a $1230.00 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. Llama 3.1 405B (base) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (33K 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 (44/100) correlates with better nuance, coherence, and style in long-form content
GPT-4 (older v0314) has a moderate advantage with a 5.799999999999997-point lead in composite score. It wins on more signal dimensions, but Llama 3.1 405B (base) has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-4 (older v0314)
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 405B (base)
91% lower pricing; better value at scale
Best for Reliability
GPT-4 (older v0314)
Higher uptime and faster response speeds
Best for Prototyping
GPT-4 (older v0314)
Stronger community support and better developer experience
Best for Production
GPT-4 (older v0314)
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4 (older v0314) | Llama 3.1 405B (base) |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Meta
Llama 3.1 405B (base) saves you $114.00/month
That's 90% cheaper than GPT-4 (older v0314) 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 (older v0314) | Llama 3.1 405B (base) |
|---|---|---|
| Context Window | 8K | 33K |
| Max Output Tokens | 4,096 | 32,768 |
| Open Source | Yes | Yes |
| Created | May 28, 2023 | Aug 2, 2024 |
GPT-4 (older v0314) scores 44/100 (rank #270) compared to Llama 3.1 405B (base)'s 38/100 (rank #283), giving it a 6-point advantage. GPT-4 (older v0314) is the stronger overall choice, though Llama 3.1 405B (base) may excel in specific areas like cost efficiency.
GPT-4 (older v0314) is ranked #270 and Llama 3.1 405B (base) is ranked #283 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 3.1 405B (base) is cheaper at $4.00/M output tokens vs GPT-4 (older v0314)'s $60.00/M output tokens — 15.0x more expensive. Input token pricing: GPT-4 (older v0314) at $30.00/M vs Llama 3.1 405B (base) at $4.00/M.
Llama 3.1 405B (base) has a larger context window of 32,768 tokens compared to GPT-4 (older v0314)'s 8,191 tokens. A larger context window means the model can process longer documents and conversations.