| Signal | GPT-5.1 | Delta | Llama 3.1 8B Instruct |
|---|---|---|---|
Capabilities | 100 | +50 | |
Pricing | 10 | +10 | |
Context window size | 89 | +22 | |
Recency | 100 | +77 | |
Output Capacity | 85 | +15 | |
Benchmarks | 0 | -40 | |
| Overall Result | 5 wins | of 6 | 1 wins |
30
days ranked higher
0
days
0
days ranked higher
OpenAI
Meta
Llama 3.1 8B Instruct saves you $620.50/month
That's $7446.00/year compared to GPT-5.1 at your current usage level of 100K calls/month.
| Metric | GPT-5.1 | Llama 3.1 8B Instruct | Winner |
|---|---|---|---|
| Overall Score | 96 | 46 | GPT-5.1 |
| Rank | #13 | #260 | GPT-5.1 |
| Quality Rank | #13 | #260 | GPT-5.1 |
| Adoption Rank | #13 | #260 | GPT-5.1 |
| Parameters | -- | 8B | -- |
| Context Window | 400K | 16K | GPT-5.1 |
| Pricing | $1.25/$10.00/M | $0.02/$0.05/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-5.1 |
| Pricing | 10 | 0 | GPT-5.1 |
| Context window size | 89 | 67 | GPT-5.1 |
| Recency | 100 | 24 | GPT-5.1 |
| Output Capacity | 85 | 70 | GPT-5.1 |
| Benchmarks | -- | 40 | Llama 3.1 8B Instruct |
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 96/100 (rank #13), placing it in the top 96% of all 290 models tracked.
Scores 46/100 (rank #260), placing it in the top 11% of all 290 models tracked.
GPT-5.1 has a 49-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Llama 3.1 8B Instruct offers 99% better value per quality point. At 1M tokens/day, you'd spend $1.05/month with Llama 3.1 8B Instruct vs $168.75/month with GPT-5.1 — a $167.70 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 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 ($0.05/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (96/100) 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-5.1 clearly outperforms Llama 3.1 8B Instruct with a significant 49.4-point lead. For most general use cases, GPT-5.1 is the stronger choice. However, Llama 3.1 8B Instruct may still excel in niche scenarios.
Best for Quality
GPT-5.1
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 8B Instruct
99% lower pricing; better value at scale
Best for Reliability
GPT-5.1
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.1
Stronger community support and better developer experience
Best for Production
GPT-5.1
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.1 | 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 $14.15/month
That's 99% cheaper than GPT-5.1 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-5.1 | Llama 3.1 8B Instruct |
|---|---|---|
| Context Window | 400K | 16K |
| Max Output Tokens | 128,000 | 16,384 |
| Open Source | No | Yes |
| Created | Nov 13, 2025 | Jul 23, 2024 |
GPT-5.1 scores 96/100 (rank #13) compared to Llama 3.1 8B Instruct's 46/100 (rank #260), giving it a 49-point advantage. GPT-5.1 is the stronger overall choice, though Llama 3.1 8B Instruct may excel in specific areas like cost efficiency.
GPT-5.1 is ranked #13 and Llama 3.1 8B Instruct is ranked #260 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 8B Instruct is cheaper at $0.05/M output tokens vs GPT-5.1's $10.00/M output tokens — 200.0x more expensive. Input token pricing: GPT-5.1 at $1.25/M vs Llama 3.1 8B Instruct at $0.02/M.
GPT-5.1 has a larger context window of 400,000 tokens compared to Llama 3.1 8B Instruct's 16,384 tokens. A larger context window means the model can process longer documents and conversations.