| Signal | Gemini 2.5 Pro Preview 05-06 | Delta | Llama 3.1 405B (base) |
|---|---|---|---|
Capabilities | 83 | +67 | |
Pricing | 10 | +6 | |
Context window size | 96 | +24 | |
Recency | 76 | +51 | |
Output Capacity | 80 | +5 | |
| Overall Result | 5 wins | of 5 | 0 wins |
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Meta
Llama 3.1 405B (base) saves you $25.00/month
That's $300.00/year compared to Gemini 2.5 Pro Preview 05-06 at your current usage level of 100K calls/month.
| Metric | Gemini 2.5 Pro Preview 05-06 | Llama 3.1 405B (base) | Winner |
|---|---|---|---|
| Overall Score | 84 | 38 | Gemini 2.5 Pro Preview 05-06 |
| Rank | #61 | #283 | Gemini 2.5 Pro Preview 05-06 |
| Quality Rank | #61 | #283 | Gemini 2.5 Pro Preview 05-06 |
| Adoption Rank | #61 | #283 | Gemini 2.5 Pro Preview 05-06 |
| Parameters | -- | 405B | -- |
| Context Window | 1049K | 33K | Gemini 2.5 Pro Preview 05-06 |
| Pricing | $1.25/$10.00/M | $4.00/$4.00/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 17 | Gemini 2.5 Pro Preview 05-06 |
| Pricing | 10 | 4 | Gemini 2.5 Pro Preview 05-06 |
| Context window size | 96 | 72 | Gemini 2.5 Pro Preview 05-06 |
| Recency | 76 | 25 | Gemini 2.5 Pro Preview 05-06 |
| Output Capacity | 80 | 75 | Gemini 2.5 Pro Preview 05-06 |
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 84/100 (rank #61), placing it in the top 79% of all 290 models tracked.
Scores 38/100 (rank #283), placing it in the top 3% of all 290 models tracked.
Gemini 2.5 Pro Preview 05-06 has a 46-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Gemini 2.5 Pro Preview 05-06 offers 29% better value per quality point. At 1M tokens/day, you'd spend $120.00/month with Llama 3.1 405B (base) vs $168.75/month with Gemini 2.5 Pro Preview 05-06 — a $48.75 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 (1049K 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 (84/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input — can analyze screenshots, diagrams, photos, and scanned documents directly
Gemini 2.5 Pro Preview 05-06 clearly outperforms Llama 3.1 405B (base) with a significant 45.599999999999994-point lead. For most general use cases, Gemini 2.5 Pro Preview 05-06 is the stronger choice. However, Llama 3.1 405B (base) may still excel in niche scenarios.
Best for Quality
Gemini 2.5 Pro Preview 05-06
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 405B (base)
29% lower pricing; better value at scale
Best for Reliability
Gemini 2.5 Pro Preview 05-06
Higher uptime and faster response speeds
Best for Prototyping
Gemini 2.5 Pro Preview 05-06
Stronger community support and better developer experience
Best for Production
Gemini 2.5 Pro Preview 05-06
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemini 2.5 Pro Preview 05-06 | Llama 3.1 405B (base) |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
Llama 3.1 405B (base) saves you $2.25/month
That's 16% cheaper than Gemini 2.5 Pro Preview 05-06 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 | Gemini 2.5 Pro Preview 05-06 | Llama 3.1 405B (base) |
|---|---|---|
| Context Window | 1.0M | 33K |
| Max Output Tokens | 65,535 | 32,768 |
| Open Source | No | Yes |
| Created | May 7, 2025 | Aug 2, 2024 |
Gemini 2.5 Pro Preview 05-06 scores 84/100 (rank #61) compared to Llama 3.1 405B (base)'s 38/100 (rank #283), giving it a 46-point advantage. Gemini 2.5 Pro Preview 05-06 is the stronger overall choice, though Llama 3.1 405B (base) may excel in specific areas like cost efficiency.
Gemini 2.5 Pro Preview 05-06 is ranked #61 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 Gemini 2.5 Pro Preview 05-06's $10.00/M output tokens — 2.5x more expensive. Input token pricing: Gemini 2.5 Pro Preview 05-06 at $1.25/M vs Llama 3.1 405B (base) at $4.00/M.
Gemini 2.5 Pro Preview 05-06 has a larger context window of 1,048,576 tokens compared to Llama 3.1 405B (base)'s 32,768 tokens. A larger context window means the model can process longer documents and conversations.