| Signal | GPT-5.2 Pro | Delta | Llama 3.1 8B Instruct |
|---|---|---|---|
Capabilities | 100 | +50 | |
Benchmarks | 89 | +45 | |
Pricing | 5 | -95 | |
Context window size | 80 | +7 | |
Recency | 97 | +92 | |
Output Capacity | 85 | +15 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
90.1
current score
GPT-5.2 Pro
right now
44.1
current score
OpenAI
Meta
Llama 3.1 8B Instruct saves you $10496.50/month
That's $125958.00/year compared to GPT-5.2 Pro at your current usage level of 100K calls/month.
| Metric | GPT-5.2 Pro | Llama 3.1 8B Instruct | Winner |
|---|---|---|---|
| Overall Score | 90 | 44 | GPT-5.2 Pro |
| Rank | #13 | #166 | GPT-5.2 Pro |
| Quality Rank | #13 | #166 | GPT-5.2 Pro |
| Adoption Rank | #13 | #166 | GPT-5.2 Pro |
| Parameters | -- | 8B | -- |
| Context Window | 400K | 131K | GPT-5.2 Pro |
| Pricing | $21.00/$168.00/M | $0.02/$0.03/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-5.2 Pro |
| Benchmarks | 89 | 44 | GPT-5.2 Pro |
| Pricing | 5 | 100 | Llama 3.1 8B Instruct |
| Context window size | 80 | 73 | GPT-5.2 Pro |
| Recency | 97 | 5 | GPT-5.2 Pro |
| Output Capacity | 85 | 70 | GPT-5.2 Pro |
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%). Learn more about our methodology.
Scores 90/100 (rank #13), placing it in the top 96% of all 290 models tracked.
Scores 44/100 (rank #166), placing it in the top 43% of all 290 models tracked.
GPT-5.2 Pro has a 46-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Llama 3.1 8B Instruct offers 100% better value per quality point. At 1M tokens/day, you'd spend $0.75/month with Llama 3.1 8B Instruct vs $2835.00/month with GPT-5.2 Pro - a $2834.25 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Llama 3.1 8B Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.03/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (90/100) 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
GPT-5.2 Pro clearly outperforms Llama 3.1 8B Instruct with a significant 45.99999999999999-point lead. For most general use cases, GPT-5.2 Pro is the stronger choice. However, Llama 3.1 8B Instruct may still excel in niche scenarios.
Best for Quality
GPT-5.2 Pro
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 8B Instruct
100% lower pricing; better value at scale
Best for Reliability
GPT-5.2 Pro
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.2 Pro
Stronger community support and better developer experience
Best for Production
GPT-5.2 Pro
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.2 Pro | Llama 3.1 8B Instruct |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Meta
Llama 3.1 8B Instruct saves you $239.33/month
That's 100% cheaper than GPT-5.2 Pro 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-5.2 Pro | Llama 3.1 8B Instruct |
|---|---|---|
| Context Window | 400K | 131K |
| Max Output Tokens | 128,000 | 16,384 |
| Open Source | No | Yes |
| Created | Dec 10, 2025 | Jul 23, 2024 |