| Signal | GPT-5.2 | Delta | Llama 3 70B Instruct |
|---|---|---|---|
Capabilities | 83 | +67 | |
Benchmarks | 89 | +29 | |
Pricing | 86 | -13 | |
Context window size | 89 | +27 | |
Recency | 100 | +100 | |
Output Capacity | 85 | +20 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
89.7
current score
GPT-5.2
right now
57
current score
OpenAI
Meta
Llama 3 70B Instruct saves you $787.00/month
That's $9444.00/year compared to GPT-5.2 at your current usage level of 100K calls/month.
| Metric | GPT-5.2 | Llama 3 70B Instruct | Winner |
|---|---|---|---|
| Overall Score | 90 | 57 | GPT-5.2 |
| Rank | #7 | #157 | GPT-5.2 |
| Quality Rank | #7 | #157 | GPT-5.2 |
| Adoption Rank | #7 | #157 | GPT-5.2 |
| Parameters | -- | 70B | -- |
| Context Window | 400K | 8K | GPT-5.2 |
| Pricing | $1.75/$14.00/M | $0.51/$0.74/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 17 | GPT-5.2 |
| Benchmarks | 89 | 60 | GPT-5.2 |
| Pricing | 86 | 99 | Llama 3 70B Instruct |
| Context window size | 89 | 62 | GPT-5.2 |
| Recency | 100 | 0 | GPT-5.2 |
| Output Capacity | 85 | 65 | GPT-5.2 |
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 #7), placing it in the top 98% of all 290 models tracked.
Scores 57/100 (rank #157), placing it in the top 46% of all 290 models tracked.
GPT-5.2 has a 33-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Llama 3 70B Instruct offers 92% better value per quality point. At 1M tokens/day, you'd spend $18.75/month with Llama 3 70B Instruct vs $236.25/month with GPT-5.2 - a $217.50 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 70B 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 ($0.74/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 clearly outperforms Llama 3 70B Instruct with a significant 32.7-point lead. For most general use cases, GPT-5.2 is the stronger choice. However, Llama 3 70B Instruct may still excel in niche scenarios.
Best for Quality
GPT-5.2
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3 70B Instruct
92% lower pricing; better value at scale
Best for Reliability
GPT-5.2
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.2
Stronger community support and better developer experience
Best for Production
GPT-5.2
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.2 | Llama 3 70B Instruct |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Meta
Llama 3 70B Instruct saves you $18.14/month
That's 91% cheaper than GPT-5.2 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 | Llama 3 70B Instruct |
|---|---|---|
| Context Window | 400K | 8K |
| Max Output Tokens | 128,000 | 8,000 |
| Open Source | No | Yes |
| Created | Dec 10, 2025 | Apr 18, 2024 |